UPSC CSE: A Probabilistic Analysis of Selection Patterns (2021\u20132024)<\/title>\n<script src=\"https:\/\/cdnjs.cloudflare.com\/ajax\/libs\/Chart.js\/4.4.1\/chart.umd.min.js\"><\/script>\n<link href=\"https:\/\/fonts.googleapis.com\/css2?family=Playfair+Display:ital,wght@0,400;0,600;0,700;1,400&family=Cormorant+Garamond:ital,wght@0,400;0,500;0,600;1,400&family=DM+Mono:wght@400&display=swap\" rel=\"stylesheet\">\n<style>\n:root {\n --ink: #1a1714;\n --parchment: #f5f0e8;\n --amber: #c17817;\n --rust: #a0522d;\n --deep-rust: #8b3a1a;\n --warm-gray: #6b5e50;\n --light-warm: #ede6d8;\n --cream: #faf6ee;\n --sage: #5a6b52;\n --border: #d4c9b8;\n --tbl-hdr: #2c2418;\n --tbl-alt: #f0e9dc;\n --highlight: rgba(193,120,23,0.08);\n --sao-color: #c17817;\n --fts-color: #5a6b52;\n --ias-color: #8b3a1a;\n --ifs-color: #c17817;\n --ips-color: #2c6e49;\n --ocs-color: #6b5e50;\n}\n*{box-sizing:border-box;margin:0;padding:0}\nbody{font-family:'Cormorant 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.val{font-family:'Playfair Display',serif;font-size:1.6em;font-weight:700;color:var(--amber)}\n\n\/* Footer *\/\n.footer-note{margin-top:48px;padding-top:28px;border-top:1px solid var(--border);font-size:.84em;color:var(--warm-gray);font-style:italic;line-height:1.6}\n.footer-note p{text-align:left}\n\n\/* Flow diagram *\/\n.flow-diagram{display:flex;flex-wrap:wrap;justify-content:center;gap:8px;margin:24px 0}\n.flow-item{background:var(--tbl-hdr);color:var(--parchment);padding:8px 14px;border-radius:20px;font-size:.82em;font-family:'DM Mono',monospace}\n.flow-arrow{color:var(--amber);font-size:1.2em;display:flex;align-items:center;padding:0 4px}\n\n\/* Progress bars *\/\n.bar-row{display:flex;align-items:center;margin:8px 0;gap:10px}\n.bar-label{width:60px;font-size:.82em;text-align:right;font-family:'DM 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Services Examination: A Probabilistic Analysis of Selection Patterns (2021\u20132024)<\/h1>\n<p class=\"subtitle\">First-Timers vs. Candidates “Selected at Least Once” \u2014 What the Data Reveals<\/p>\n<\/div>\n\n\n<div class=\"disclaimer\">\n<strong>\u26a0 Disclaimer<\/strong><br>\n<strong>This analysis is generated with AI assistance.<\/strong> The data has been parsed from official UPSC service allocation lists (2020\u20132024) using automated name-matching algorithms. The analysis is intended purely for educational and informational purposes \u2014 to help candidates understand examination patterns, probabilities, and trends. <strong>This document should NOT be used to make career decisions, financial decisions, or life choices.<\/strong> Candidates are advised to consult mentors, career counsellors, and official UPSC resources before making any decisions regarding their examination strategy. <strong>The Author has also written the exam thrice in years 2002, 2003, 2004 and got selected for IPoS, IPS and IAS, and firmly believes all civil services are created equal, but perceived differently because of various notions in society and culture. All services provide equal opportunity to keep the bureaucratic machine of the Indian Government running, which in turn is subservient to the will of the people.<\/strong>\n<\/div>\n\n\n<div style=\"background:var(--light-warm);border:1px solid var(--border);border-radius:8px;padding:28px 32px;margin:32px 0\">\n<h3 style=\"font-family:'Playfair Display',serif;color:var(--deep-rust);margin:0 0 16px;font-size:1.3em\">Index of Chapters<\/h3>\n<div style=\"display:grid;grid-template-columns:1fr 1fr;gap:6px 24px;font-size:.95em\">\n<a href=\"#methodology\" style=\"padding:6px 0;border-bottom:none;color:var(--ink);display:flex;gap:8px\"><span style=\"color:var(--amber);font-family:'DM Mono',monospace;font-size:.85em;min-width:24px\">\u00a7<\/span> Assumptions and Methodology<\/a>\n<a href=\"#ch5\" style=\"padding:6px 0;border-bottom:none;color:var(--ink);display:flex;gap:8px\"><span style=\"color:var(--amber);font-family:'DM Mono',monospace;font-size:.85em;min-width:24px\">5<\/span> UPSC CSE 2026 Notification \u2014 Restricting Re-Attempts<\/a>\n<a href=\"#ch1\" style=\"padding:6px 0;border-bottom:none;color:var(--ink);display:flex;gap:8px\"><span style=\"color:var(--amber);font-family:'DM Mono',monospace;font-size:.85em;min-width:24px\">1<\/span> The Examination Funnel \u2014 Apply, Write, Get Selected<\/a>\n<a href=\"#ch6\" style=\"padding:6px 0;border-bottom:none;color:var(--ink);display:flex;gap:8px\"><span style=\"color:var(--amber);font-family:'DM Mono',monospace;font-size:.85em;min-width:24px\">6<\/span> Economics of Repetition \u2014 Opportunity Costs & Superannuation<\/a>\n<a href=\"#ch2\" style=\"padding:6px 0;border-bottom:none;color:var(--ink);display:flex;gap:8px\"><span style=\"color:var(--amber);font-family:'DM Mono',monospace;font-size:.85em;min-width:24px\">2<\/span> The “Selected at Least Once” Phenomenon<\/a>\n<a href=\"#ch7\" style=\"padding:6px 0;border-bottom:none;color:var(--ink);display:flex;gap:8px\"><span style=\"color:var(--amber);font-family:'DM Mono',monospace;font-size:.85em;min-width:24px\">7<\/span> Why Give Your Best Shot \u2014 The Repeated First Attempt<\/a>\n<a href=\"#ch3\" style=\"padding:6px 0;border-bottom:none;color:var(--ink);display:flex;gap:8px\"><span style=\"color:var(--amber);font-family:'DM Mono',monospace;font-size:.85em;min-width:24px\">3<\/span> Adjacent-Year Re-Selection \u2014 Immediate Return Cycle<\/a>\n<a href=\"#\" style=\"padding:6px 0;border-bottom:none;color:transparent;pointer-events:none\"> <\/a>\n<a href=\"#ch4\" style=\"padding:6px 0;border-bottom:none;color:var(--ink);display:flex;gap:8px\"><span style=\"color:var(--amber);font-family:'DM Mono',monospace;font-size:.85em;min-width:24px\">4<\/span> Service Selection Probability \u2014 FTS vs. SAO<\/a>\n<\/div>\n<p style=\"font-size:.82em;color:var(--warm-gray);margin:14px 0 0;font-style:italic\">\u00a7 3.4 covers adjacent-year (Y\u2192Y+1) transitions only | \u00a7 4.3 covers lifetime first-to-last trajectories across the full 2020\u20132024 window<\/p>\n<\/div>\n\n\n<h2 id=\"methodology\">Assumptions and Methodology<\/h2>\n<div class=\"method-box\">\n<ol>\n<li><strong>Name-based matching<\/strong>: Candidates appearing across multiple years are identified by matching cleaned, standardised names (uppercase, special characters removed, whitespace collapsed). Minor spelling variations may cause missed matches (false negatives); common names may produce false positives.<\/li>\n<li><strong>Data cleaning<\/strong>: Two categories of data quality issues were identified and addressed:\n<br>\u2014 <strong>True duplicates<\/strong> (same name + same service appearing twice in the same year): 10 such rows removed.\n<br>\u2014 <strong>Ambiguous common names<\/strong> (same name with <em>different<\/em> services in the same year \u2014 different individuals): 33 such names excluded from all cross-year matching.<\/li>\n<li><strong>Reference year vs. analysis years<\/strong>: <strong>CSE 2020<\/strong> (673 usable candidates) is used solely as a <strong>reference year<\/strong>. The 2020 cohort is <strong>not<\/strong> itself analysed. All analysis covers <strong>CSE 2021, 2022, 2023, and 2024<\/strong>.<\/li>\n<li><strong>“Selected at Least Once” (SAO)<\/strong>: Candidates whose names also appear in any prior year’s allocation list (2020 onward).<\/li>\n<li><strong>“First-Time Selectees”<\/strong>: Names that do NOT appear in any prior year’s list. They may not be first-time exam takers \u2014 only first-time selectees within our detection range.<\/li>\n<li><strong>“Adjacent-year re-selector”<\/strong>: Selected in year Y and also in Y+1 \u2014 actual name-matching.<\/li>\n<li><strong>Aggregate statistics<\/strong> from PIB press releases and UPSC annual reports; approximate where exact figures unavailable.<\/li>\n<li><strong>No category or reservation data<\/strong> used. All figures are all-category aggregates.<\/li>\n<li><strong>Service grouping<\/strong>: IAS, IFS, IPS, and “Other Central Services” (IRS-IT, IRS-C&IT, IRMS, IDAS, IA&AS, ICLS, IIS, IPoS, DANICS, DANIPS, IDES, ITS, IRPFS, IP&TAFS, ICAS, AFHQ, PONDICS, etc.).<\/li>\n<li><strong>Service hierarchy<\/strong>: IAS > IFS > IPS > Other Central Services.<\/li>\n<li><strong>Financial calculations<\/strong> use the 7th CPC pay matrix and standard investment return assumptions.<\/li>\n<\/ol>\n<\/div>\n\n\n<h3>Data Cleaning Summary<\/h3>\n<table>\n<thead><tr><th>Year<\/th><th>Raw Records<\/th><th>Dups Removed<\/th><th>Clean<\/th><th>Ambiguous Flagged<\/th><th>Usable<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>2020<\/td><td class=\"num\">688<\/td><td class=\"num\">2<\/td><td class=\"num\">686<\/td><td class=\"num\">13<\/td><td class=\"num\">673<\/td><\/tr>\n<tr><td>2021<\/td><td class=\"num\">659<\/td><td class=\"num\">2<\/td><td class=\"num\">657<\/td><td class=\"num\">14<\/td><td class=\"num\">643<\/td><\/tr>\n<tr><td>2022<\/td><td class=\"num\">784<\/td><td class=\"num\">3<\/td><td class=\"num\">781<\/td><td class=\"num\">14<\/td><td class=\"num\">767<\/td><\/tr>\n<tr><td>2023<\/td><td class=\"num\">995<\/td><td class=\"num\">1<\/td><td class=\"num\">994<\/td><td class=\"num\">39<\/td><td class=\"num\">955<\/td><\/tr>\n<tr><td>2024<\/td><td class=\"num\">965<\/td><td class=\"num\">2<\/td><td class=\"num\">963<\/td><td class=\"num\">25<\/td><td class=\"num\">938<\/td><\/tr>\n<tr><td><strong>Total<\/strong><\/td><td class=\"num\"><strong>4,091<\/strong><\/td><td class=\"num\"><strong>10<\/strong><\/td><td class=\"num\"><strong>4,081<\/strong><\/td><td class=\"num\"><strong>\u2014<\/strong><\/td><td class=\"num\"><strong>3,976<\/strong><\/td><\/tr>\n<\/tbody>\n<\/table>\n<p>33 ambiguous names (common names like ASHISH KUMAR, SANDEEP KUMAR, NIDHI, etc. appearing with different services in the same year) were excluded from all cross-year matching. Full list documented in the accompanying Excel workbook.<\/p>\n\n<div class=\"separator\">\u2022 \u2022 \u2022<\/div>\n\n\n<h2 id=\"ch1\"><span class=\"chapter-label\">Chapter One<\/span>The Examination Funnel \u2014 How Many Apply, Write, and Get Selected?<\/h2>\n\n<h3>1.1 Year-Wise Examination Statistics<\/h3>\n<table>\n<thead><tr><th>Year<\/th><th>Applied (Approx.)<\/th><th>Appeared Prelims<\/th><th>Qualified Mains<\/th><th>Interviewed<\/th><th>Finally Selected<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>2020<\/td><td class=\"num\">~10,58,000<\/td><td class=\"num\">~4,82,000<\/td><td class=\"num\">~10,564<\/td><td class=\"num\">~2,100<\/td><td class=\"num\">761<\/td><\/tr>\n<tr><td>2021<\/td><td class=\"num\">~10,93,984<\/td><td class=\"num\">~5,09,113<\/td><td class=\"num\">~10,000<\/td><td class=\"num\">~2,080<\/td><td class=\"num\">712<\/td><\/tr>\n<tr><td>2022<\/td><td class=\"num\">~11,52,566<\/td><td class=\"num\">~5,73,735<\/td><td class=\"num\">~13,090<\/td><td class=\"num\">~2,529<\/td><td class=\"num\">933<\/td><\/tr>\n<tr><td>2023<\/td><td class=\"num\">~13,35,697<\/td><td class=\"num\">~6,50,000<\/td><td class=\"num\">~14,624<\/td><td class=\"num\">~2,916<\/td><td class=\"num\">1,016<\/td><\/tr>\n<tr><td>2024<\/td><td class=\"num\">~9,92,599<\/td><td class=\"num\">~5,83,213<\/td><td class=\"num\">~14,627<\/td><td class=\"num\">~2,845<\/td><td class=\"num\">1,009<\/td><\/tr>\n<\/tbody>\n<\/table>\n<p style=\"font-size:.85em;color:var(--warm-gray);font-style:italic\">Sources: PIB press releases, UPSC Annual Reports.<\/p>\n\n<h3>1.2 Stage-Wise Elimination Probabilities<\/h3>\n\n\n<div class=\"funnel\">\n<div class=\"funnel-step\" style=\"width:90%;background:var(--tbl-hdr)\">~10.9 Lakh Applied<span class=\"detail\">Average across 2020\u20132024<\/span><\/div>\n<div class=\"funnel-arrow\">\u25bc ~50\u201355% appearance rate<\/div>\n<div class=\"funnel-step\" style=\"width:72%;background:var(--deep-rust)\">~5.8 Lakh Appeared for Prelims<\/div>\n<div class=\"funnel-arrow\">\u25bc ~1.5\u20132.5% qualification rate<\/div>\n<div class=\"funnel-step\" style=\"width:38%;background:var(--rust)\">~14,000 Qualified for Mains<\/div>\n<div class=\"funnel-arrow\">\u25bc ~19\u201322% interview rate<\/div>\n<div class=\"funnel-step\" style=\"width:22%;background:var(--amber)\">~2,800 Called for Interview<\/div>\n<div class=\"funnel-arrow\">\u25bc ~33\u201340% selection rate<\/div>\n<div class=\"funnel-step\" style=\"width:14%;background:var(--sage)\">~1,000 Finally Selected<\/div>\n<\/div>\n\n<table>\n<thead><tr><th>Stage Transition<\/th><th>Approx. Probability<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>Applied \u2192 Appeared for Prelims<\/td><td class=\"pct\">~50\u201355%<\/td><\/tr>\n<tr><td>Appeared Prelims \u2192 Qualified for Mains<\/td><td class=\"pct\">~1.5\u20132.5%<\/td><\/tr>\n<tr><td>Qualified Mains \u2192 Called for Interview<\/td><td class=\"pct\">~19\u201322%<\/td><\/tr>\n<tr><td>Interviewed \u2192 Finally Selected<\/td><td class=\"pct\">~33\u201340%<\/td><\/tr>\n<tr><td><strong>Applied \u2192 Finally Selected<\/strong><\/td><td class=\"pct\"><strong>~0.07\u20130.10%<\/strong><\/td><\/tr>\n<tr><td><strong>Appeared Prelims \u2192 Finally Selected<\/strong><\/td><td class=\"pct\"><strong>~0.13\u20130.20%<\/strong><\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<p>The Preliminary Examination eliminates approximately 97\u201398% of candidates who appear. Once a candidate reaches the interview stage, the selection rate improves to roughly one-in-three \u2014 the Mains examination is the true differentiator.<\/p>\n\n<h3>1.3 Parsed Allocation Data<\/h3>\n<table>\n<thead><tr><th>Year<\/th><th>Role in This Analysis<\/th><th>Usable Candidates<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>2020<\/td><td><strong>Reference year<\/strong> (not analysed)<\/td><td class=\"num\">673<\/td><\/tr>\n<tr><td>2021<\/td><td>Analysis year<\/td><td class=\"num\">643<\/td><\/tr>\n<tr><td>2022<\/td><td>Analysis year<\/td><td class=\"num\">767<\/td><\/tr>\n<tr><td>2023<\/td><td>Analysis year<\/td><td class=\"num\">955<\/td><\/tr>\n<tr><td>2024<\/td><td>Analysis year<\/td><td class=\"num\">938<\/td><\/tr>\n<tr><td><strong>2021\u20132024 Total<\/strong><\/td><td>\u2014<\/td><td class=\"num\"><strong>3,303<\/strong><\/td><\/tr>\n<\/tbody>\n<\/table>\n<p>The 3,303 usable allocations across the four analysis years represent <strong>2,939 unique individuals<\/strong>. An additional 673 usable individuals in the 2020 reference year provide the baseline against which “Selected at Least Once” status is determined.<\/p>\n\n<div class=\"separator\">\u2022 \u2022 \u2022<\/div>\n\n\n<h2 id=\"ch2\"><span class=\"chapter-label\">Chapter Two<\/span>The “Selected at Least Once” Phenomenon \u2014 Repetition Across Years<\/h2>\n\n<h3>2.1 Year-Wise Composition: First-Time Selectees vs. Selected at Least Once<\/h3>\n<p>For each analysis year, a candidate is classified as “Selected at Least Once” (SAO) if their name appears in any prior year’s allocation list (starting from 2020). Only usable (non-ambiguous) names are classified.<\/p>\n\n<table>\n<thead><tr><th>Year<\/th><th>Total Selected<\/th><th>Usable<\/th><th>First-Time Selectees<\/th><th>SAO<\/th><th>% First-Time<\/th><th>% SAO<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>2021<\/td><td class=\"num\">657<\/td><td class=\"num\">643<\/td><td class=\"num\">586<\/td><td class=\"num\">57<\/td><td class=\"pct\">91.1%<\/td><td class=\"pct\">8.9%<\/td><\/tr>\n<tr><td>2022<\/td><td class=\"num\">781<\/td><td class=\"num\">767<\/td><td class=\"num\">666<\/td><td class=\"num\">101<\/td><td class=\"pct\">86.8%<\/td><td class=\"pct\">13.2%<\/td><\/tr>\n<tr><td>2023<\/td><td class=\"num\">994<\/td><td class=\"num\">955<\/td><td class=\"num\">808<\/td><td class=\"num\">147<\/td><td class=\"pct\">84.6%<\/td><td class=\"pct\">15.4%<\/td><\/tr>\n<tr><td>2024<\/td><td class=\"num\">963<\/td><td class=\"num\">938<\/td><td class=\"num\">743<\/td><td class=\"num\">195<\/td><td class=\"pct\">79.2%<\/td><td class=\"pct\"><strong>20.8%<\/strong><\/td><\/tr>\n<\/tbody>\n<\/table>\n\n\n<div class=\"chart-container\">\n<div class=\"chart-title\">SAO Proportion Growing Steadily (2021\u20132024)<\/div>\n<canvas id=\"saoTrendChart\" height=\"280\"><\/canvas>\n<div class=\"chart-note\">2021 SAO (8.9%) based on 1-year lookback; 2024 (20.8%) based on 4-year lookback \u2014 most reliable figure.<\/div>\n<\/div>\n\n<p>The proportion of SAO candidates has grown steadily from 8.9% in 2021 to <strong>20.8% in 2024<\/strong>. By 2024, approximately <strong>one in five usable selectees<\/strong> had already been selected in at least one prior year.<\/p>\n<p><em>Note: The 2021 SAO figure (8.9%) is based on only one year of lookback (2020). The true SAO proportion in 2021 is likely higher, as candidates selected before 2020 are invisible to our detection. The 2024 figure (20.8%), with four years of lookback, is the most complete and reliable.<\/em><\/p>\n\n<h3>2.2 Unique Candidate Summary (2021\u20132024)<\/h3>\n\n<div class=\"stat-grid\">\n<div class=\"stat-card\"><span class=\"big\">2,939<\/span><span class=\"label\">Unique Individuals (usable)<\/span><\/div>\n<div class=\"stat-card\"><span class=\"big\">456<\/span><span class=\"label\">Selected at Least Once (15.5%)<\/span><\/div>\n<div class=\"stat-card\"><span class=\"big\">2,483<\/span><span class=\"label\">First-Time Selectees (84.5%)<\/span><\/div>\n<div class=\"stat-card\"><span class=\"big\">364<\/span><span class=\"label\">Re-selection Instances<\/span><\/div>\n<\/div>\n\n<table>\n<thead><tr><th>Metric<\/th><th>Count<\/th><th>%<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>Total unique individuals in 2021\u20132024 (usable)<\/td><td class=\"num\">2,939<\/td><td class=\"pct\">100%<\/td><\/tr>\n<tr><td>Of these, also appeared in 2020 reference year<\/td><td class=\"num\">136<\/td><td class=\"pct\">4.6%<\/td><\/tr>\n<tr><td>Multi-selected within 2021\u20132024 (appeared 2+ times)<\/td><td class=\"num\">344<\/td><td class=\"pct\">11.7%<\/td><\/tr>\n<tr><td>Total “Selected at Least Once” unique individuals<\/td><td class=\"num\">456<\/td><td class=\"pct\">15.5%<\/td><\/tr>\n<tr><td>Purely first-time selectee individuals<\/td><td class=\"num\">2,483<\/td><td class=\"pct\">84.5%<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<h3>2.3 Frequency of Re-Selection (Within 2021\u20132024)<\/h3>\n\n<div class=\"chart-container\" style=\"max-width:500px\">\n<div class=\"chart-title\">Selection Frequency Distribution<\/div>\n<canvas id=\"freqChart\" height=\"250\"><\/canvas>\n<\/div>\n\n<table>\n<thead><tr><th>Times Selected in 2021\u20132024<\/th><th>Candidates<\/th><th>%<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>1 time<\/td><td class=\"num\">2,595<\/td><td class=\"pct\">88.3%<\/td><\/tr>\n<tr><td>2 times<\/td><td class=\"num\">326<\/td><td class=\"pct\">11.1%<\/td><\/tr>\n<tr><td>3 times<\/td><td class=\"num\">16<\/td><td class=\"pct\">0.5%<\/td><\/tr>\n<tr><td>4 times (all four years)<\/td><td class=\"num\">2<\/td><td class=\"pct\">0.1%<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<p>Total re-selection instances (usable allocations minus unique individuals) = <strong>364<\/strong> across the four analysis years. These 364 “seat-opportunities” were consumed by candidates who had already been allocated a service at least once before.<\/p>\n\n<h3>2.4 Year-Pair Overlap Matrix (Usable Names Only)<\/h3>\n\n<div class=\"chart-container\">\n<div class=\"chart-title\">Cross-Year Overlap \u2014 Candidates Appearing in Both Years<\/div>\n<canvas id=\"overlapChart\" height=\"280\"><\/canvas>\n<div class=\"chart-note\">Adjacent years show highest overlap; diminishes with distance as candidates exit the cycle.<\/div>\n<\/div>\n\n<table>\n<thead><tr><th><\/th><th>2020<\/th><th>2021<\/th><th>2022<\/th><th>2023<\/th><th>2024<\/th><\/tr><\/thead>\n<tbody>\n<tr><td><strong>2020<\/strong><\/td><td class=\"num\">673<\/td><td class=\"num\">57<\/td><td class=\"num\">49<\/td><td class=\"num\">29<\/td><td class=\"num\">25<\/td><\/tr>\n<tr><td><strong>2021<\/strong><\/td><td class=\"num\">57<\/td><td class=\"num\">643<\/td><td class=\"num\">56<\/td><td class=\"num\">47<\/td><td class=\"num\">21<\/td><\/tr>\n<tr><td><strong>2022<\/strong><\/td><td class=\"num\">49<\/td><td class=\"num\">56<\/td><td class=\"num\">767<\/td><td class=\"num\">87<\/td><td class=\"num\">73<\/td><\/tr>\n<tr><td><strong>2023<\/strong><\/td><td class=\"num\">29<\/td><td class=\"num\">47<\/td><td class=\"num\">87<\/td><td class=\"num\">955<\/td><td class=\"num\">102<\/td><\/tr>\n<tr><td><strong>2024<\/strong><\/td><td class=\"num\">25<\/td><td class=\"num\">21<\/td><td class=\"num\">73<\/td><td class=\"num\">102<\/td><td class=\"num\">938<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<h3>2.5 Implications<\/h3>\n\n<div class=\"callout\">\nFor every 1,000 usable seats in 2024, approximately <strong>208 were taken by returning selectees<\/strong>, leaving roughly <strong>792 for new entrants<\/strong>. Across the four analysis years, <strong>364 seat-opportunities<\/strong> were consumed by re-selection.\n<\/div>\n\n<div class=\"separator\">\u2022 \u2022 \u2022<\/div>\n\n\n<h2 id=\"ch3\"><span class=\"chapter-label\">Chapter Three<\/span>Adjacent-Year Re-Selection \u2014 The Immediate Return Cycle and Service Improvement Probability<\/h2>\n\n<p>This chapter examines candidates selected in year Y who re-appear in year Y+1 \u2014 the most consequential form of re-attempting. All figures are from actual name-matching on usable (non-ambiguous) names only.<\/p>\n\n<h3>3.1 Adjacent-Year Re-Selection Rates<\/h3>\n<table>\n<thead><tr><th>Year Pair<\/th><th>Usable Y1<\/th><th>Usable Y2<\/th><th>Overlap<\/th><th>Re-Sel Rate (% Y1)<\/th><th>% Y2 Seats<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>2020 \u2192 2021<\/td><td class=\"num\">673<\/td><td class=\"num\">643<\/td><td class=\"num\">57<\/td><td class=\"pct\">8.5%<\/td><td class=\"pct\">8.9%<\/td><\/tr>\n<tr><td>2021 \u2192 2022<\/td><td class=\"num\">643<\/td><td class=\"num\">767<\/td><td class=\"num\">56<\/td><td class=\"pct\">8.7%<\/td><td class=\"pct\">7.3%<\/td><\/tr>\n<tr><td>2022 \u2192 2023<\/td><td class=\"num\">767<\/td><td class=\"num\">955<\/td><td class=\"num\">87<\/td><td class=\"pct\">11.3%<\/td><td class=\"pct\">9.1%<\/td><\/tr>\n<tr><td>2023 \u2192 2024<\/td><td class=\"num\">955<\/td><td class=\"num\">938<\/td><td class=\"num\">102<\/td><td class=\"pct\">10.7%<\/td><td class=\"pct\">10.9%<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<p>Approximately <strong>8.5\u201311.3% of each year’s selectees<\/strong> re-appear in the very next cycle, consuming <strong>7.3\u201310.9% of the next year’s seats<\/strong>. The rate has been trending upward.<\/p>\n\n<h3>3.2 Where Do Adjacent-Year Re-Selectors Come From?<\/h3>\n\n<div class=\"chart-container\">\n<div class=\"chart-title\">Prior Service of Adjacent-Year Re-Selectors<\/div>\n<canvas id=\"feederChart\" height=\"260\"><\/canvas>\n<div class=\"chart-note\">~66\u201376% consistently from Central Services; ~19\u201332% from IPS<\/div>\n<\/div>\n\n<table>\n<thead><tr><th>Year Pair<\/th><th>From Other Central Services<\/th><th>From IPS<\/th><th>From IAS<\/th><th>From IFS<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>2020 \u2192 2021<\/td><td class=\"num\">40 (70.2%)<\/td><td class=\"num\">13 (22.8%)<\/td><td class=\"num\">3 (5.3%)<\/td><td class=\"num\">1 (1.8%)<\/td><\/tr>\n<tr><td>2021 \u2192 2022<\/td><td class=\"num\">37 (66.1%)<\/td><td class=\"num\">18 (32.1%)<\/td><td class=\"num\">1 (1.8%)<\/td><td class=\"num\">0 (0.0%)<\/td><\/tr>\n<tr><td>2022 \u2192 2023<\/td><td class=\"num\">63 (72.4%)<\/td><td class=\"num\">17 (19.5%)<\/td><td class=\"num\">7 (8.0%)<\/td><td class=\"num\">0 (0.0%)<\/td><\/tr>\n<tr><td>2023 \u2192 2024<\/td><td class=\"num\">77 (75.5%)<\/td><td class=\"num\">21 (20.6%)<\/td><td class=\"num\">3 (2.9%)<\/td><td class=\"num\">1 (1.0%)<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<h3>3.3 Service Improvement Probability<\/h3>\n\n<div class=\"chart-container\">\n<div class=\"chart-title\">Outcome of Adjacent-Year Re-Selection: Did They Upgrade?<\/div>\n<canvas id=\"upgradeChart\" height=\"260\"><\/canvas>\n<\/div>\n\n<table>\n<thead><tr><th>Year Pair<\/th><th>Re-Selected<\/th><th>Upgraded<\/th><th>Same Tier<\/th><th>Different Tier<\/th><th>Upgrade Rate<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>2020 \u2192 2021<\/td><td class=\"num\">57<\/td><td class=\"num\">39<\/td><td class=\"num\">12<\/td><td class=\"num\">6<\/td><td class=\"pct\"><strong>68.4%<\/strong><\/td><\/tr>\n<tr><td>2021 \u2192 2022<\/td><td class=\"num\">56<\/td><td class=\"num\">33<\/td><td class=\"num\">17<\/td><td class=\"num\">6<\/td><td class=\"pct\"><strong>58.9%<\/strong><\/td><\/tr>\n<tr><td>2022 \u2192 2023<\/td><td class=\"num\">87<\/td><td class=\"num\">50<\/td><td class=\"num\">27<\/td><td class=\"num\">10<\/td><td class=\"pct\"><strong>57.5%<\/strong><\/td><\/tr>\n<tr><td>2023 \u2192 2024<\/td><td class=\"num\">102<\/td><td class=\"num\">64<\/td><td class=\"num\">31<\/td><td class=\"num\">7<\/td><td class=\"pct\"><strong>62.7%<\/strong><\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<p><strong>~58\u201368% of adjacent-year re-selectors achieve a service upgrade.<\/strong> But ~21\u201331% remain in the same tier, and ~7\u201311% move to a different tier in the opposite direction.<\/p>\n\n<h3>3.4 Service Transitions in the Immediate Next Year \u2014 Aggregated Across All Four Adjacent Pairs<\/h3>\n\n<p>The table below shows where candidates moved when re-selected <strong>in the very next examination cycle (Y \u2192 Y+1 only)<\/strong>. This captures only the immediate one-year return pattern.<\/p>\n\n<div class=\"chart-container\">\n<div class=\"chart-title\">Adjacent-Year Service Transitions Only (Y \u2192 Y+1, All Four Pairs Combined)<\/div>\n<canvas id=\"transChart\" height=\"320\"><\/canvas>\n<\/div>\n\n<table>\n<thead><tr><th>Transition (Y \u2192 Y+1)<\/th><th>Count<\/th><th>Direction<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>Other Central Services \u2192 Other Central Services<\/td><td class=\"num\">76<\/td><td>\u2192 Same tier<\/td><\/tr>\n<tr><td>Other Central Services \u2192 IAS<\/td><td class=\"num\">68<\/td><td>\u2191 Upgrade<\/td><\/tr>\n<tr><td>Other Central Services \u2192 IPS<\/td><td class=\"num\">61<\/td><td>\u2191 Upgrade<\/td><\/tr>\n<tr><td>IPS \u2192 IAS<\/td><td class=\"num\">36<\/td><td>\u2191 Upgrade<\/td><\/tr>\n<tr><td>IPS \u2192 Other Central Services<\/td><td class=\"num\">19<\/td><td>\u2193 Different tier<\/td><\/tr>\n<tr><td>Other Central Services \u2192 IFS<\/td><td class=\"num\">12<\/td><td>\u2191 Upgrade<\/td><\/tr>\n<tr><td>IPS \u2192 IFS<\/td><td class=\"num\">8<\/td><td>\u2191 Upgrade<\/td><\/tr>\n<tr><td>IPS \u2192 IPS<\/td><td class=\"num\">6<\/td><td>\u2192 Same tier<\/td><\/tr>\n<tr><td>IAS \u2192 Other Central Services<\/td><td class=\"num\">6<\/td><td>\u2193 Different tier<\/td><\/tr>\n<tr><td>IAS \u2192 IAS<\/td><td class=\"num\">5<\/td><td>\u2192 Same tier<\/td><\/tr>\n<tr><td>IAS \u2192 IPS<\/td><td class=\"num\">3<\/td><td>\u2192 Mixed<\/td><\/tr>\n<tr><td>IFS \u2192 IAS<\/td><td class=\"num\">1<\/td><td>\u2191 Upgrade<\/td><\/tr>\n<tr><td>IFS \u2192 IPS<\/td><td class=\"num\">1<\/td><td>\u2192 Mixed<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<p>The most frequent transition pathways: <strong>Central Services \u2192 IAS<\/strong> (68), <strong>Central Services \u2192 IPS<\/strong> (61), <strong>IPS \u2192 IAS<\/strong> (36) \u2014 accounting for 165 of 186 total service changes to a higher-ranked group.<\/p>\n\n<h3>3.5 IAS Selection Rate Among Re-Selectors<\/h3>\n<table>\n<thead><tr><th>Year Pair<\/th><th>Re-Selectors<\/th><th>Selected into IAS<\/th><th>IAS Selection Rate<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>2020 \u2192 2021<\/td><td class=\"num\">57<\/td><td class=\"num\">24<\/td><td class=\"pct\"><strong>42.1%<\/strong><\/td><\/tr>\n<tr><td>2021 \u2192 2022<\/td><td class=\"num\">56<\/td><td class=\"num\">21<\/td><td class=\"pct\"><strong>37.5%<\/strong><\/td><\/tr>\n<tr><td>2022 \u2192 2023<\/td><td class=\"num\">87<\/td><td class=\"num\">29<\/td><td class=\"pct\"><strong>33.3%<\/strong><\/td><\/tr>\n<tr><td>2023 \u2192 2024<\/td><td class=\"num\">102<\/td><td class=\"num\">36<\/td><td class=\"pct\"><strong>35.3%<\/strong><\/td><\/tr>\n<\/tbody>\n<\/table>\n<p><strong>One-third to two-fifths<\/strong> of adjacent-year re-selectors are allocated IAS in their subsequent selection \u2014 a proportion notably higher than the ~18% share IAS represents in the overall allocation.<\/p>\n\n<h3>3.6 The Non-Adjacent Gap: Skipping a Year<\/h3>\n<table>\n<thead><tr><th>Gap Pair<\/th><th>Total Overlap<\/th><th>Skipped Middle Year<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>2020 \u2192 2022 (skipped 2021)<\/td><td class=\"num\">49<\/td><td class=\"num\">45<\/td><\/tr>\n<tr><td>2021 \u2192 2023 (skipped 2022)<\/td><td class=\"num\">47<\/td><td class=\"num\">41<\/td><\/tr>\n<tr><td>2022 \u2192 2024 (skipped 2023)<\/td><td class=\"num\">73<\/td><td class=\"num\">62<\/td><\/tr>\n<\/tbody>\n<\/table>\n<p>Substantial numbers skip a year and return \u2014 the re-attempt cycle is a persistent, multi-year phenomenon.<\/p>\n\n<h3>3.7 Summary<\/h3>\n<div class=\"stat-grid\">\n<div class=\"stat-card\"><span class=\"big\">8.5\u201311.3%<\/span><span class=\"label\">of selectees re-appear next cycle<\/span><\/div>\n<div class=\"stat-card\"><span class=\"big\">~70%<\/span><span class=\"label\">come from Central Services<\/span><\/div>\n<div class=\"stat-card\"><span class=\"big\">~62%<\/span><span class=\"label\">achieve service upgrade<\/span><\/div>\n<div class=\"stat-card\"><span class=\"big\">~36%<\/span><span class=\"label\">are allocated IAS<\/span><\/div>\n<\/div>\n\n<div class=\"separator\">\u2022 \u2022 \u2022<\/div>\n\n\n<h2 id=\"ch4\"><span class=\"chapter-label\">Chapter Four<\/span>Service Selection Probability \u2014 First-Time Selectees vs. Selected at Least Once<\/h2>\n\n<h3>4.1 Service-Wise Breakdown by Year<\/h3>\n\n<h4>CSE 2021<\/h4>\n<table>\n<thead><tr><th>Service Group<\/th><th>Usable<\/th><th>First-Time Selectees<\/th><th>SAO<\/th><th>% First-Time<\/th><th>% SAO<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>IAS<\/td><td class=\"num\">175<\/td><td class=\"num\">151<\/td><td class=\"num\">24<\/td><td class=\"pct\">86.3%<\/td><td class=\"pct\">13.7%<\/td><\/tr>\n<tr><td>IFS<\/td><td class=\"num\">36<\/td><td class=\"num\">33<\/td><td class=\"num\">3<\/td><td class=\"pct\">91.7%<\/td><td class=\"pct\">8.3%<\/td><\/tr>\n<tr><td>IPS<\/td><td class=\"num\">197<\/td><td class=\"num\">179<\/td><td class=\"num\">18<\/td><td class=\"pct\">90.9%<\/td><td class=\"pct\">9.1%<\/td><\/tr>\n<tr><td>Other Central Services<\/td><td class=\"num\">235<\/td><td class=\"num\">223<\/td><td class=\"num\">12<\/td><td class=\"pct\">94.9%<\/td><td class=\"pct\">5.1%<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<h4>CSE 2022<\/h4>\n<table>\n<thead><tr><th>Service Group<\/th><th>Usable<\/th><th>First-Time Selectees<\/th><th>SAO<\/th><th>% First-Time<\/th><th>% SAO<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>IAS<\/td><td class=\"num\">157<\/td><td class=\"num\">122<\/td><td class=\"num\">35<\/td><td class=\"pct\">77.7%<\/td><td class=\"pct\">22.3%<\/td><\/tr>\n<tr><td>IFS<\/td><td class=\"num\">29<\/td><td class=\"num\">25<\/td><td class=\"num\">4<\/td><td class=\"pct\">86.2%<\/td><td class=\"pct\">13.8%<\/td><\/tr>\n<tr><td>IPS<\/td><td class=\"num\">170<\/td><td class=\"num\">148<\/td><td class=\"num\">22<\/td><td class=\"pct\">87.1%<\/td><td class=\"pct\">12.9%<\/td><\/tr>\n<tr><td>Other Central Services<\/td><td class=\"num\">411<\/td><td class=\"num\">371<\/td><td class=\"num\">40<\/td><td class=\"pct\">90.3%<\/td><td class=\"pct\">9.7%<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<h4>CSE 2023<\/h4>\n<table>\n<thead><tr><th>Service Group<\/th><th>Usable<\/th><th>First-Time Selectees<\/th><th>SAO<\/th><th>% First-Time<\/th><th>% SAO<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>IAS<\/td><td class=\"num\">174<\/td><td class=\"num\">128<\/td><td class=\"num\">46<\/td><td class=\"pct\">73.6%<\/td><td class=\"pct\">26.4%<\/td><\/tr>\n<tr><td>IFS<\/td><td class=\"num\">36<\/td><td class=\"num\">28<\/td><td class=\"num\">8<\/td><td class=\"pct\">77.8%<\/td><td class=\"pct\">22.2%<\/td><\/tr>\n<tr><td>IPS<\/td><td class=\"num\">190<\/td><td class=\"num\">157<\/td><td class=\"num\">33<\/td><td class=\"pct\">82.6%<\/td><td class=\"pct\">17.4%<\/td><\/tr>\n<tr><td>Other Central Services<\/td><td class=\"num\">555<\/td><td class=\"num\">495<\/td><td class=\"num\">60<\/td><td class=\"pct\">89.2%<\/td><td class=\"pct\">10.8%<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<h4>CSE 2024<\/h4>\n<table>\n<thead><tr><th>Service Group<\/th><th>Usable<\/th><th>First-Time Selectees<\/th><th>SAO<\/th><th>% First-Time<\/th><th>% SAO<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>IAS<\/td><td class=\"num\">170<\/td><td class=\"num\">106<\/td><td class=\"num\">64<\/td><td class=\"pct\">62.4%<\/td><td class=\"pct\"><strong>37.6%<\/strong><\/td><\/tr>\n<tr><td>IFS<\/td><td class=\"num\">52<\/td><td class=\"num\">37<\/td><td class=\"num\">15<\/td><td class=\"pct\">71.2%<\/td><td class=\"pct\"><strong>28.8%<\/strong><\/td><\/tr>\n<tr><td>IPS<\/td><td class=\"num\">145<\/td><td class=\"num\">104<\/td><td class=\"num\">41<\/td><td class=\"pct\">71.7%<\/td><td class=\"pct\"><strong>28.3%<\/strong><\/td><\/tr>\n<tr><td>Other Central Services<\/td><td class=\"num\">571<\/td><td class=\"num\">496<\/td><td class=\"num\">75<\/td><td class=\"pct\">86.9%<\/td><td class=\"pct\">13.1%<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<h3>4.2 Proportion of SAO Candidates in IAS Over Time<\/h3>\n\n<div class=\"chart-container\">\n<div class=\"chart-title\">SAO Proportion by Service Group (2021\u20132024)<\/div>\n<canvas id=\"svcSaoChart\" height=\"280\"><\/canvas>\n<\/div>\n\n<table>\n<thead><tr><th>Year<\/th><th>IAS Usable<\/th><th>SAO in IAS<\/th><th>% SAO<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>2021<\/td><td class=\"num\">175<\/td><td class=\"num\">24<\/td><td class=\"pct\">13.7%<\/td><\/tr>\n<tr><td>2022<\/td><td class=\"num\">157<\/td><td class=\"num\">35<\/td><td class=\"pct\">22.3%<\/td><\/tr>\n<tr><td>2023<\/td><td class=\"num\">174<\/td><td class=\"num\">46<\/td><td class=\"pct\">26.4%<\/td><\/tr>\n<tr><td>2024<\/td><td class=\"num\">170<\/td><td class=\"num\">64<\/td><td class=\"pct\"><strong>37.6%<\/strong><\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<p>By 2024, nearly <strong>four out of every ten IAS seats<\/strong> (among usable names) went to candidates who had been selected in a prior year. The steady acceleration from 13.7% to 37.6% over four years is consistent.<\/p>\n\n<h3>4.3 Lifetime Service Trajectory of All 456 SAO Candidates \u2014 First Selection to Most Recent (Full 2020\u20132024 Window)<\/h3>\n<p>Unlike Section 3.4 (which tracked only adjacent-year Y \u2192 Y+1 transitions), this section traces each SAO candidate’s <strong>entire journey from their first-ever selection to their most recent selection<\/strong> across the full five-year window. A candidate selected in 2020, 2022, and 2024 is represented here as a single trajectory from their 2020 service to their 2024 service \u2014 regardless of what happened in between.<\/p>\n<p>Among the 456 SAO candidates (usable, 2+ selections, present in 2021\u20132024):<\/p>\n\n<table>\n<thead><tr><th>First Service \u2192 Most Recent Service<\/th><th>Count<\/th><th>Interpretation<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>Other Central Services \u2192 Other Central Services<\/td><td class=\"num\">119<\/td><td>Same tier<\/td><\/tr>\n<tr><td>Other Central Services \u2192 IAS<\/td><td class=\"num\">106<\/td><td>Moved to IAS<\/td><\/tr>\n<tr><td>Other Central Services \u2192 IPS<\/td><td class=\"num\">85<\/td><td>Moved to IPS<\/td><\/tr>\n<tr><td>IPS \u2192 IAS<\/td><td class=\"num\">50<\/td><td>Moved from IPS to IAS<\/td><\/tr>\n<tr><td>IPS \u2192 Other Central Services<\/td><td class=\"num\">32<\/td><td>Cadre\/rank preference<\/td><\/tr>\n<tr><td>Other Central Services \u2192 IFS<\/td><td class=\"num\">20<\/td><td>Moved to IFS<\/td><\/tr>\n<tr><td>IAS \u2192 Other Central Services<\/td><td class=\"num\">11<\/td><td>Name-matching noise likely<\/td><\/tr>\n<tr><td>IPS \u2192 IFS<\/td><td class=\"num\">10<\/td><td>Moved from IPS to IFS<\/td><\/tr>\n<tr><td>IAS \u2192 IPS<\/td><td class=\"num\">8<\/td><td>Lateral<\/td><\/tr>\n<tr><td>IPS \u2192 IPS<\/td><td class=\"num\">6<\/td><td>Same service<\/td><\/tr>\n<tr><td>IAS \u2192 IAS<\/td><td class=\"num\">6<\/td><td>Same<\/td><\/tr>\n<tr><td>IFS \u2192 various<\/td><td class=\"num\">3<\/td><td>Very rare<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<div class=\"chart-container\">\n<div class=\"chart-title\">Overall Trajectory Outcomes \u2014 456 SAO Candidates<\/div>\n<canvas id=\"trajChart\" height=\"250\"><\/canvas>\n<\/div>\n\n<table>\n<thead><tr><th>Outcome<\/th><th>Count<\/th><th>% of All SAO<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>Upgraded service<\/td><td class=\"num\">272<\/td><td class=\"pct\">59.6%<\/td><\/tr>\n<tr><td>Same service tier<\/td><td class=\"num\">131<\/td><td class=\"pct\">28.7%<\/td><\/tr>\n<tr><td>Moved to different tier<\/td><td class=\"num\">53<\/td><td class=\"pct\">11.6%<\/td><\/tr>\n<tr><td><strong>Final service = IAS<\/strong><\/td><td class=\"num\"><strong>163<\/strong><\/td><td class=\"pct\"><strong>35.7%<\/strong><\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<p>163 of 456 SAO candidates (35.7%) ultimately ended up in IAS. This means that nearly <strong>two-thirds of SAO candidates did not achieve the IAS allocation<\/strong> despite being selected multiple times.<\/p>\n\n<h3>4.4 What This Means for a First-Time Selectee Targeting IAS<\/h3>\n<div class=\"callout\">\nA first-time selectee targeting IAS in 2024 is competing for approximately <strong>106 first-time selectee IAS seats<\/strong> out of 170 usable total \u2014 the remaining 64 were taken by SAO candidates. The effective competition for first-time selectee IAS seats is substantially more intense than the headline numbers suggest.\n<\/div>\n\n<div class=\"separator\">\u2022 \u2022 \u2022<\/div>\n\n\n<h2 id=\"ch5\"><span class=\"chapter-label\">Chapter Five<\/span>The UPSC CSE 2026 Notification \u2014 Restricting Re-Attempts by Serving Officers<\/h2>\n\n<h3>5.1 What Changed<\/h3>\n<p>The UPSC CSE 2026 notification (February 4, 2026) introduced landmark changes:<\/p>\n\n<div class=\"compare-grid\">\n<div class=\"compare-card\">\n<h4>Pre-2026 Rules<\/h4>\n<p><strong>IAS\/IFS officers<\/strong>: Permitted to attempt exam while serving.<\/p>\n<p><strong>IPS officers<\/strong>: Permitted to attempt and opt for IPS again.<\/p>\n<p><strong>Central Services<\/strong>: Unlimited attempts within age\/attempt limits.<\/p>\n<\/div>\n<div class=\"compare-card\" style=\"border-color:var(--deep-rust)\">\n<h4>Post-2026 Rules<\/h4>\n<p><strong>IAS\/IFS officers<\/strong>: Completely barred. Resignation mandatory.<\/p>\n<p><strong>IPS officers<\/strong>: Can attempt, but cannot be allocated IPS again.<\/p>\n<p><strong>Central Services<\/strong>: One-time improvement window only. Non-repeatable.<\/p>\n<p><strong>2028 cutoff<\/strong>: Resignation mandatory for any serving officer to re-attempt.<\/p>\n<\/div>\n<\/div>\n\n<h3>5.2 Seats Not Available for First-Time Selectees Due to “Selected at Least Once” Candidates<\/h3>\n<p>Our cleaned data shows that 20.8% of 2024 selections and 37.6% of IAS seats went to SAO candidates. The adjacent-year data (Chapter 3) shows ~8.5\u201311.3% of selectees immediately re-appear, with ~66\u201376% from Central Services and ~19\u201332% from IPS. Each repeated selection creates a cascading displacement chain through the service ladder.<\/p>\n\n<h3>5.3 Projected Impact<\/h3>\n<p>If the 2026 rules had been in effect, approximately <strong>~125 additional seats per year<\/strong> (averaging across the four analysis years) would have been freed for first-time selectees. For IAS, approximately <strong>~44 additional first-time selectee seats<\/strong> per year \u2014 a meaningful improvement in selection probability.<\/p>\n\n<h3>5.4 The Debate<\/h3>\n<p>Proponents argue for a more level playing field for first-time selectees. Critics counter that restrictions may limit legitimate career choices. UPSC’s stated rationale: administrative efficiency, training resource optimisation, and fairness to new entrants.<\/p>\n\n<div class=\"separator\">\u2022 \u2022 \u2022<\/div>\n\n\n<h2 id=\"ch6\"><span class=\"chapter-label\">Chapter Six<\/span>The Economics of Repetition \u2014 Opportunity Costs, Near-Term Salary Loss, and Superannuation Penalties<\/h2>\n\n<p>Engaging in repeated examination cycles carries a profound financial penalty \u2014 the <strong>opportunity cost<\/strong>. This manifests in two devastating phases: the immediate hemorrhage of near-future earnings, and the compounding destruction of terminal wealth and pension benefits at superannuation.<\/p>\n\n<h3>6.1 The Financial Architecture of the Civil Services (7th Pay Commission)<\/h3>\n<p>Promotions are bound to <strong>years of service<\/strong>, not age or rank. This makes the year of entry the single most consequential financial variable in an officer’s career.<\/p>\n\n<div class=\"ladder\">\n<div class=\"ladder-step\"><span class=\"level\">Level 18<\/span><span class=\"desc\">Cabinet Secretary (37+ yrs)<\/span><span class=\"pay\">\u20b92,50,000<\/span><\/div>\n<div class=\"ladder-step\"><span class=\"level\">Level 17<\/span><span class=\"desc\">Apex Scale (34\u201336 yrs)<\/span><span class=\"pay\">\u20b92,25,000<\/span><\/div>\n<div class=\"ladder-step\"><span class=\"level\">Level 15<\/span><span class=\"desc\">Above Super Time Scale (25\u201330 yrs)<\/span><span class=\"pay\">\u20b91,82,200<\/span><\/div>\n<div class=\"ladder-step\"><span class=\"level\">Level 14<\/span><span class=\"desc\">Super Time Scale (16\u201324 yrs)<\/span><span class=\"pay\">\u20b91,44,200<\/span><\/div>\n<div class=\"ladder-step\"><span class=\"level\">Level 12<\/span><span class=\"desc\">Jr. Administrative Grade (9\u201312 yrs)<\/span><span class=\"pay\">\u20b978,800<\/span><\/div>\n<div class=\"ladder-step\"><span class=\"level\">Level 11<\/span><span class=\"desc\">Senior Time Scale (4\u20139 yrs)<\/span><span class=\"pay\">\u20b967,700<\/span><\/div>\n<div class=\"ladder-step\" style=\"border-left-color:var(--sage)\"><span class=\"level\">Level 10<\/span><span class=\"desc\">Junior Scale \u2014 Entry Level (0\u20134 yrs)<\/span><span class=\"pay\">\u20b956,100<\/span><\/div>\n<\/div>\n<p style=\"font-size:.85em;color:var(--warm-gray);font-style:italic;text-align:center\">Gross monthly at entry scales to \u20b990,000\u2013\u20b91,00,000 with DA, HRA, and TA.<\/p>\n\n<h3>6.2 The Near-Term Salary Haemorrhage<\/h3>\n<table>\n<thead><tr><th>Delay Period<\/th><th>Salary Foregone (Govt.)<\/th><th>Salary Foregone (Private, Premier Grad.)<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>1 year<\/td><td class=\"num\">\u20b910\u201312 lakh<\/td><td class=\"num\">\u20b98\u201315 lakh<\/td><\/tr>\n<tr><td>2 years<\/td><td class=\"num\">\u20b920\u201324 lakh<\/td><td class=\"num\">\u20b918\u201332 lakh<\/td><\/tr>\n<tr><td>3 years<\/td><td class=\"num\">\u20b930\u201336 lakh<\/td><td class=\"num\">\u20b928\u201350 lakh<\/td><\/tr>\n<tr><td>5 years<\/td><td class=\"num\">\u20b955\u201365 lakh<\/td><td class=\"num\">\u20b960\u20131.0 crore<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<h3>6.3 The Mathematics of Compounding: Wealth Destruction Through Delay<\/h3>\n<p><strong>Candidate A<\/strong> \u2014 Enters workforce at 23. Invests \u20b940,000\/month (10% return) for 5 years (age 23\u201328), then stops adding money.<\/p>\n<p><strong>Candidate B<\/strong> \u2014 Prepares full-time ages 23\u201328. Zero income. Enters service at 28.<\/p>\n\n<table>\n<thead><tr><th>Financial Metric<\/th><th>Candidate A (Enters at 23)<\/th><th>Candidate B (Enters at 28)<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>Action, age 23\u201328<\/td><td>Works, invests \u20b940,000\/month<\/td><td>Studies. \u20b90 income, \u20b90 invested<\/td><\/tr>\n<tr><td>Capital by age 28<\/td><td class=\"num\">\u20b924 lakh (principal)<\/td><td class=\"num\">\u20b90<\/td><\/tr>\n<tr><td>Action, age 28\u201360<\/td><td>Stops adding. Lets corpus compound 32 years<\/td><td>Starts working. Must catch up<\/td><\/tr>\n<tr><td><strong>Corpus at 60 from early investment alone<\/strong><\/td><td class=\"pct\"><strong>~\u20b95.25 crore<\/strong><\/td><td class=\"num\"><strong>\u20b90 from this window<\/strong><\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<p>Candidate A’s \u20b924 lakh grows to over <strong>\u20b95 crore<\/strong> purely from time-in-market. The five years of lost compounding destroys roughly <strong>\u20b92 crore<\/strong> from this tranche alone.<\/p>\n\n<h3>6.4 Full Career Compounding Impact<\/h3>\n\n<div class=\"chart-container\">\n<div class=\"chart-title\">Compounding Curves: Candidate A (37 yrs) vs Candidate B (32 yrs)<\/div>\n<canvas id=\"compoundChart\" height=\"280\"><\/canvas>\n<div class=\"chart-note\">10% CAGR, \u20b95L starting annual savings, 5% annual increment. A ends at ~\u20b931Cr, B at ~\u20b918Cr. Delta: ~\u20b913 crore at age 60.<\/div>\n<\/div>\n\n<table>\n<thead><tr><th>Parameter<\/th><th>Candidate A (37 years)<\/th><th>Candidate B (32 years)<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>Total investment years<\/td><td class=\"num\">37<\/td><td class=\"num\">32<\/td><\/tr>\n<tr><td>Starting annual savings<\/td><td class=\"num\">\u20b95,00,000<\/td><td class=\"num\">\u20b95,00,000<\/td><\/tr>\n<tr><td>Annual increment<\/td><td class=\"num\">5%<\/td><td class=\"num\">5%<\/td><\/tr>\n<tr><td>Return rate<\/td><td class=\"num\">10% CAGR<\/td><td class=\"num\">10% CAGR<\/td><\/tr>\n<tr><td><strong>Corpus at age 60<\/strong><\/td><td class=\"pct\"><strong>~\u20b931.0 crore<\/strong><\/td><td class=\"num\">~\u20b918.2 crore<\/td><\/tr>\n<tr><td><strong>Difference<\/strong><\/td><td colspan=\"2\" style=\"text-align:center\" class=\"pct\"><strong>~\u20b912.8 crore less<\/strong><\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<h3>6.5 The Superannuation Penalty \u2014 The Career Ceiling Effect<\/h3>\n<table>\n<thead><tr><th>Entry Age<\/th><th>Years of Service (Retire at 60)<\/th><th>Terminal Pay Level<\/th><th>Terminal Basic Pay<\/th><\/tr><\/thead>\n<tbody>\n<tr><td class=\"num\">23<\/td><td class=\"num\">37 years<\/td><td>Level 17\u201318 (Apex \/ Cabinet Secy.)<\/td><td class=\"num\">\u20b92,25,000\u2013\u20b92,50,000<\/td><\/tr>\n<tr><td class=\"num\">25<\/td><td class=\"num\">35 years<\/td><td>Level 17 (Apex Scale)<\/td><td class=\"num\">\u20b92,25,000<\/td><\/tr>\n<tr><td class=\"num\">28<\/td><td class=\"num\">32 years<\/td><td>Level 15\u201316<\/td><td class=\"num\">\u20b91,82,200\u2013\u20b92,05,400<\/td><\/tr>\n<tr><td class=\"num\">30<\/td><td class=\"num\">30 years<\/td><td>Level 14\u201315<\/td><td class=\"num\">\u20b91,44,200\u2013\u20b91,82,200<\/td><\/tr>\n<tr><td class=\"num\">32<\/td><td class=\"num\">28 years<\/td><td>Level 14<\/td><td class=\"num\">\u20b91,44,200<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<p>Because <strong>pensions are derived from the last drawn salary<\/strong>, years spent preparing for exams directly amputate the highest-paying years \u2014 a <strong>lifelong financial penalty<\/strong> extending into retirement. The pension differential between Level 15 and Level 17 is approximately <strong>\u20b940,000\u2013\u20b965,000 per month<\/strong>, or <strong>\u20b95\u20138 lakh per year<\/strong>. Over a 20\u201325 year retirement, this exceeds <strong>\u20b91\u20132 crore<\/strong>.<\/p>\n\n<h3>6.6 The Private Sector Comparison<\/h3>\n<p>A premier-institution graduate taking a private sector job at 23, investing \u20b94 lakh\/year at 10% for 37 years with 8% annual increment, accumulates approximately <strong>\u20b912\u201315 crore<\/strong> \u2014 comparable to or exceeding civil services, with more career flexibility and no examination stress. The point is not that private employment is superior \u2014 civil services offer irreplaceable public impact and constitutional authority \u2014 but the financial cost of delay is <strong>substantial, mathematically irreversible, and almost universally underestimated<\/strong>.<\/p>\n\n<h3>6.7 Total Cost of a 5-Year Delay<\/h3>\n\n<div class=\"stat-grid\">\n<div class=\"stat-card\"><span class=\"big\">\u20b955\u201365L<\/span><span class=\"label\">Direct salary foregone<\/span><\/div>\n<div class=\"stat-card\"><span class=\"big\">\u20b92\u201313Cr<\/span><span class=\"label\">Lost compounding<\/span><\/div>\n<div class=\"stat-card\"><span class=\"big\">1\u20132 levels<\/span><span class=\"label\">Reduced terminal pay<\/span><\/div>\n<div class=\"stat-card\"><span class=\"big\">\u20b91\u20132Cr<\/span><span class=\"label\">Pension loss (20 yrs)<\/span><\/div>\n<\/div>\n\n<table>\n<thead><tr><th>Cost Component<\/th><th>Approximate Value<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>Direct salary foregone (5 years)<\/td><td class=\"num\">\u20b955\u201365 lakh<\/td><\/tr>\n<tr><td>Lost compounding on early-career savings<\/td><td class=\"num\">\u20b92\u201313 crore<\/td><\/tr>\n<tr><td>Reduced terminal pay level<\/td><td>1\u20132 pay levels lower<\/td><\/tr>\n<tr><td>Cumulative pension loss over 20-year retirement<\/td><td class=\"num\">\u20b91\u20132 crore<\/td><\/tr>\n<tr><td><strong>Total lifetime financial impact<\/strong><\/td><td class=\"pct\"><strong>\u20b94\u201317 crore<\/strong><\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<p>The years between 22 and 28 are the <strong>most financially consequential years<\/strong> of an officer’s career \u2014 they sit at the base of the compounding curve.<\/p>\n\n<div class=\"separator\">\u2022 \u2022 \u2022<\/div>\n\n\n<h2 id=\"ch7\"><span class=\"chapter-label\">Chapter Seven<\/span>Why Candidates Should Give Their Best Shot at the First Attempt \u2014 or the Repeated First Attempt<\/h2>\n\n<h3>7.1 The Data Makes the Case<\/h3>\n<p>The analysis converges on a single insight: <strong>the examination rewards decisive, well-prepared attempts over prolonged, incremental re-tries.<\/strong><\/p>\n\n<h3>7.2 The Odds Do Not Improve with Repetition<\/h3>\n<p><strong>Syllabus evolution<\/strong>: Current affairs are entirely new each cycle. Additional years add the burden of staying current alongside deepening existing knowledge.<\/p>\n<p><strong>Diminishing returns<\/strong>: The first 6\u201312 months yield the steepest improvement. Subsequent years show diminishing marginal gains.<\/p>\n<p><strong>Psychological erosion<\/strong>: Self-doubt, comparison anxiety, and burnout can reduce performance in subsequent attempts, creating a vicious cycle.<\/p>\n\n<h3>7.3 The “Repeated First Attempt” Philosophy<\/h3>\n<p>The most successful candidates treat <strong>every attempt as if it’s their only one<\/strong> \u2014 100% preparation intensity each cycle. The data supports this: <strong>88.3%<\/strong> of unique individuals in our analysis years appear only once in the allocation lists.<\/p>\n\n<h3>7.4 The Changing Regulatory Landscape<\/h3>\n<p>CSE 2026 introduces strict re-attempt restrictions. The “join a lower service, upgrade later” strategy now carries: mandatory resignation from CSE 2028 onward, loss of seniority, a single one-time improvement window, and the psychological burden of having something to lose.<\/p>\n\n<h3>7.5 The Adjacent-Year Evidence (Chapter 3 Revisited)<\/h3>\n<p>Even among the most determined re-selectors \u2014 those returning in the very next year \u2014 only ~58\u201368% achieve a service upgrade. ~33\u201342% are allocated IAS in the subsequent selection. The remaining ~32\u201342% stay in the same tier or move to a different one.<\/p>\n\n<h3>7.6 A Framework for Decision-Making<\/h3>\n<p>Before re-attempting, evaluate honestly:<\/p>\n<p><strong>Marginal benefit<\/strong>: Is the target service significantly different in career satisfaction and lifestyle? IPS, IFS, and Central Services offer deeply fulfilling careers.<\/p>\n<p><strong>Marginal cost<\/strong>: A 3-year delay costs several crores in terminal wealth. A 5-year delay can destroy \u20b94\u201317 crore in lifetime financial value \u2014 including lost compounding, reduced terminal pay, and diminished pension.<\/p>\n<p><strong>Marginal probability<\/strong>: Of 456 SAO candidates, only 163 (35.7%) ultimately landed in IAS \u2014 nearly two-thirds did not achieve the IAS allocation despite multiple selections.<\/p>\n<p><strong>Changing rules<\/strong>: CSE 2026 norms introduce resignation risk, training disruption, and irreversible administrative consequences.<\/p>\n\n<h3>7.7 The Bottom Line<\/h3>\n<div class=\"callout\">\nEvery attempt is precious. Every year of career is irreplaceable. The numbers are clear: <strong>prepare well, execute decisively, and make your attempt count.<\/strong>\n<\/div>\n\n<div class=\"separator\">\u2767<\/div>\n\n\n<div class=\"footer-note\">\n<p><strong>Analysis<\/strong>: Purushottam B. | <strong>Data<\/strong>: UPSC Service Allocation Lists 2020\u20132024 | <strong>AI Assistance<\/strong>: Claude (Anthropic)<\/p>\n<p><strong>Methodology<\/strong>: Official UPSC service allocation files for CSE 2020\u20132024 parsed using Python (pandas). Names standardised to uppercase with special characters removed. <strong>Data cleaning<\/strong>: 10 true duplicate rows removed; 33 ambiguous common names excluded from all cross-year matching. CSE 2020 (673 usable candidates) used as reference year. Analysis covers CSE 2021\u20132024 (3,303 usable allocations, 2,939 unique individuals). Adjacent-year and service trajectory analyses based on actual name-matching of usable names only. Aggregate examination statistics from PIB press releases.<\/p>\n<p>Published on <a href=\"https:\/\/basavapurushottam.com\">Stories Through Data<\/a> (basavapurushottam.com)<\/p>\n<\/div>\n\n<\/article>\n\n\n\n\n<script>\nconst amber='#c17817',rust='#a0522d',deepRust='#8b3a1a',sage='#5a6b52',warmGray='#6b5e50',cream='#faf6ee',ink='#1a1714',parchment='#f5f0e8';\nChart.defaults.font.family=\"'Cormorant Garamond',Georgia,serif\";\nChart.defaults.font.size=13;\nChart.defaults.color=ink;\n\n\/\/ Ch2: SAO Trend\nnew Chart(document.getElementById('saoTrendChart'),{\n type:'bar',\n data:{\n labels:['2021','2022','2023','2024'],\n datasets:[\n {label:'First-Time Selectees',data:[586,666,808,743],backgroundColor:sage,order:2},\n {label:'Selected at Least Once',data:[57,101,147,195],backgroundColor:amber,order:2},\n {label:'SAO %',data:[8.9,13.2,15.4,20.8],type:'line',borderColor:deepRust,backgroundColor:'transparent',pointBackgroundColor:deepRust,pointRadius:5,borderWidth:2.5,yAxisID:'pct',order:1}\n ]\n },\n options:{\n responsive:true,\n scales:{\n x:{stacked:true,grid:{display:false}},\n y:{stacked:true,title:{display:true,text:'Candidates'},grid:{color:'#e0d8cc'}},\n pct:{position:'right',min:0,max:30,title:{display:true,text:'SAO %'},ticks:{callback:v=>v+'%'},grid:{display:false}}\n },\n plugins:{legend:{position:'bottom',labels:{padding:16}}}\n }\n});\n\n\/\/ Ch2: Frequency Donut\nnew Chart(document.getElementById('freqChart'),{\n type:'doughnut',\n data:{\n labels:['1 time (88.3%)','2 times (11.1%)','3 times (0.5%)','4 times (0.1%)'],\n datasets:[{data:[2595,326,16,2],backgroundColor:[sage,amber,rust,deepRust],borderWidth:2,borderColor:cream}]\n },\n options:{responsive:true,plugins:{legend:{position:'bottom',labels:{padding:12}}}}\n});\n\n\/\/ Ch2: Overlap heatmap as grouped bar\nnew Chart(document.getElementById('overlapChart'),{\n type:'bar',\n data:{\n labels:['2020\u219221','2020\u219222','2020\u219223','2020\u219224','2021\u219222','2021\u219223','2021\u219224','2022\u219223','2022\u219224','2023\u219224'],\n datasets:[{label:'Shared Candidates',data:[57,49,29,25,56,47,21,87,73,102],backgroundColor:function(ctx){return ctx.dataIndex>=7?amber:ctx.dataIndex>=4?rust:warmGray}}]\n },\n options:{\n responsive:true,indexAxis:'y',\n scales:{x:{grid:{color:'#e0d8cc'},title:{display:true,text:'Candidates in Common'}},y:{grid:{display:false}}},\n plugins:{legend:{display:false}}\n }\n});\n\n\/\/ Ch3: Feeder service stacked\nnew Chart(document.getElementById('feederChart'),{\n type:'bar',\n data:{\n labels:['2020\u219221','2021\u219222','2022\u219223','2023\u219224'],\n datasets:[\n {label:'From Central Services',data:[40,37,63,77],backgroundColor:warmGray},\n {label:'From IPS',data:[13,18,17,21],backgroundColor:sage},\n {label:'From IAS',data:[3,1,7,3],backgroundColor:amber},\n {label:'From IFS',data:[1,0,0,1],backgroundColor:rust}\n ]\n },\n options:{\n responsive:true,scales:{x:{stacked:true,grid:{display:false}},y:{stacked:true,grid:{color:'#e0d8cc'},title:{display:true,text:'Candidates'}}},\n plugins:{legend:{position:'bottom',labels:{padding:12}}}\n }\n});\n\n\/\/ Ch3: Upgrade outcome\nnew Chart(document.getElementById('upgradeChart'),{\n type:'bar',\n data:{\n labels:['2020\u219221','2021\u219222','2022\u219223','2023\u219224'],\n datasets:[\n {label:'Upgraded',data:[39,33,50,64],backgroundColor:sage},\n {label:'Same Tier',data:[12,17,27,31],backgroundColor:amber},\n {label:'Different Tier',data:[6,6,10,7],backgroundColor:rust}\n ]\n },\n options:{\n responsive:true,scales:{x:{stacked:true,grid:{display:false}},y:{stacked:true,grid:{color:'#e0d8cc'},title:{display:true,text:'Candidates'}}},\n plugins:{legend:{position:'bottom',labels:{padding:12}}}\n }\n});\n\n\/\/ Ch3: Transitions horizontal bar\nnew Chart(document.getElementById('transChart'),{\n type:'bar',\n data:{\n labels:['OCS\u2192OCS','OCS\u2192IAS','OCS\u2192IPS','IPS\u2192IAS','IPS\u2192OCS','OCS\u2192IFS','IPS\u2192IFS','IPS\u2192IPS','IAS\u2192OCS','IAS\u2192IAS','IAS\u2192IPS','IFS\u2192IAS','IFS\u2192IPS'],\n datasets:[{\n data:[76,68,61,36,19,12,8,6,6,5,3,1,1],\n backgroundColor:function(ctx){\n const ups=[1,2,3,5,6];const same=[0,7,9];\n if(ups.includes(ctx.dataIndex))return sage;\n if(same.includes(ctx.dataIndex))return amber;\n return rust;\n }\n }]\n },\n options:{\n responsive:true,indexAxis:'y',\n scales:{x:{grid:{color:'#e0d8cc'},title:{display:true,text:'Count'}},y:{grid:{display:false},ticks:{font:{size:11}}}},\n plugins:{legend:{display:false}}\n }\n});\n\n\/\/ Ch4: SAO % by service over time\nnew Chart(document.getElementById('svcSaoChart'),{\n type:'line',\n data:{\n labels:['2021','2022','2023','2024'],\n datasets:[\n {label:'IAS',data:[13.7,22.3,26.4,37.6],borderColor:deepRust,backgroundColor:'transparent',pointBackgroundColor:deepRust,pointRadius:5,borderWidth:2.5,tension:.3},\n {label:'IFS',data:[8.3,13.8,22.2,28.8],borderColor:amber,backgroundColor:'transparent',pointBackgroundColor:amber,pointRadius:5,borderWidth:2,tension:.3},\n {label:'IPS',data:[9.1,12.9,17.4,28.3],borderColor:sage,backgroundColor:'transparent',pointBackgroundColor:sage,pointRadius:5,borderWidth:2,tension:.3},\n {label:'Other Central Services',data:[5.1,9.7,10.8,13.1],borderColor:warmGray,backgroundColor:'transparent',pointBackgroundColor:warmGray,pointRadius:4,borderWidth:1.5,borderDash:[5,3],tension:.3}\n ]\n },\n options:{\n responsive:true,\n scales:{y:{min:0,max:45,ticks:{callback:v=>v+'%'},grid:{color:'#e0d8cc'},title:{display:true,text:'% SAO'}},x:{grid:{display:false}}},\n plugins:{legend:{position:'bottom',labels:{padding:14}}}\n }\n});\n\n\/\/ Ch4: Trajectory donut\nnew Chart(document.getElementById('trajChart'),{\n type:'doughnut',\n data:{\n labels:['Upgraded (59.6%)','Same Tier (28.7%)','Different Tier (11.6%)'],\n datasets:[{data:[272,131,53],backgroundColor:[sage,amber,rust],borderWidth:2,borderColor:cream}]\n },\n options:{responsive:true,plugins:{legend:{position:'bottom',labels:{padding:14}}}}\n});\n\n\/\/ Ch6: Compounding curves \u2014 Section 6.4: Full career continuous saving\n\/\/ A saves continuously age 23\u201360 (37 years), B saves continuously age 28\u201360 (32 years)\n\/\/ Both: \u20b95L\/year starting, 5% annual increment, 10% CAGR\n(function(){\n const labels=[],a=[],b=[];\n let corpusA=0,corpusB=0,savA=500000,savB=500000;\n for(let age=23;age<=60;age++){\n labels.push(age);\n \/\/ A saves every year from 23 onward\n corpusA = corpusA * 1.10 + savA;\n savA *= 1.05;\n \/\/ B only starts saving from age 28\n if(age >= 28){\n corpusB = corpusB * 1.10 + savB;\n savB *= 1.05;\n }\n a.push(Math.round(corpusA\/1000000)\/10);\n b.push(Math.round(corpusB\/1000000)\/10);\n }\n new Chart(document.getElementById('compoundChart'),{\n type:'line',\n data:{\n labels:labels,\n datasets:[\n {label:'Candidate A (enters at 23)',data:a,borderColor:sage,backgroundColor:'rgba(90,107,82,0.1)',fill:true,pointRadius:0,borderWidth:2.5,tension:.3},\n {label:'Candidate B (enters at 28)',data:b,borderColor:rust,backgroundColor:'rgba(160,82,45,0.1)',fill:true,pointRadius:0,borderWidth:2.5,tension:.3}\n ]\n },\n options:{\n responsive:true,\n scales:{\n x:{title:{display:true,text:'Age'},grid:{display:false},ticks:{callback:function(v,i){return i%5===0?labels[i]:''}}},\n y:{title:{display:true,text:'Corpus (\u20b9 Crore)'},grid:{color:'#e0d8cc'},ticks:{callback:v=>'\u20b9'+v+'Cr'}}\n },\n plugins:{legend:{position:'bottom',labels:{padding:14}}}\n }\n });\n})();\n<\/script>\n\n<\/body>\n<\/html>\n","protected":false},"excerpt":{"rendered":"<p>UPSC CSE: A Probabilistic Analysis of Selection Patterns (2021\u20132024) UPSC Civil Services Examination: A Probabilistic Analysis of Selection Patterns (2021\u20132024) First-Timers vs. Candidates “Selected at Least Once” \u2014 What the Data Reveals \u26a0 Disclaimer This analysis is generated with AI assistance. The data has been parsed from official UPSC service allocation lists (2020\u20132024) using automated […]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"off","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[1],"tags":[176],"class_list":["post-3087","post","type-post","status-publish","format-standard","hentry","category-blog","tag-upsc"],"_links":{"self":[{"href":"https:\/\/basavapurushottam.com\/index.php\/wp-json\/wp\/v2\/posts\/3087","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/basavapurushottam.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/basavapurushottam.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/basavapurushottam.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/basavapurushottam.com\/index.php\/wp-json\/wp\/v2\/comments?post=3087"}],"version-history":[{"count":2,"href":"https:\/\/basavapurushottam.com\/index.php\/wp-json\/wp\/v2\/posts\/3087\/revisions"}],"predecessor-version":[{"id":3089,"href":"https:\/\/basavapurushottam.com\/index.php\/wp-json\/wp\/v2\/posts\/3087\/revisions\/3089"}],"wp:attachment":[{"href":"https:\/\/basavapurushottam.com\/index.php\/wp-json\/wp\/v2\/media?parent=3087"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/basavapurushottam.com\/index.php\/wp-json\/wp\/v2\/categories?post=3087"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/basavapurushottam.com\/index.php\/wp-json\/wp\/v2\/tags?post=3087"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}

{"id":3087,"date":"2026-03-17T00:43:07","date_gmt":"2026-03-17T00:43:07","guid":{"rendered":"https:\/\/basavapurushottam.com\/?p=3087"},"modified":"2026-03-17T03:30:28","modified_gmt":"2026-03-17T03:30:28","slug":"selection-patterns-and-economic-variables-in-the-civil-services-examination-a-probabilistic-assessment-of-service-allocations-and-opportunity-costs-2021-2024","status":"publish","type":"post","link":"https:\/\/basavapurushottam.com\/index.php\/2026\/03\/17\/selection-patterns-and-economic-variables-in-the-civil-services-examination-a-probabilistic-assessment-of-service-allocations-and-opportunity-costs-2021-2024\/","title":{"rendered":"Selection Patterns and Economic Variables in the Civil Services Examination: A Probabilistic Assessment of Service Allocations and Opportunity Costs (2021\u20132024)"},"content":{"rendered":"\n\n\n\n\n\nUPSC CSE: A Probabilistic Analysis of Selection Patterns (2021\u20132024)<\/title>\n<script 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Services Examination: A Probabilistic Analysis of Selection Patterns (2021\u20132024)<\/h1>\n<p class=\"subtitle\">First-Timers vs. Candidates “Selected at Least Once” \u2014 What the Data Reveals<\/p>\n<\/div>\n\n\n<div class=\"disclaimer\">\n<strong>\u26a0 Disclaimer<\/strong><br>\n<strong>This analysis is generated with AI assistance.<\/strong> The data has been parsed from official UPSC service allocation lists (2020\u20132024) using automated name-matching algorithms. The analysis is intended purely for educational and informational purposes \u2014 to help candidates understand examination patterns, probabilities, and trends. <strong>This document should NOT be used to make career decisions, financial decisions, or life choices.<\/strong> Candidates are advised to consult mentors, career counsellors, and official UPSC resources before making any decisions regarding their examination strategy. <strong>The Author has also written the exam thrice in years 2002, 2003, 2004 and got selected for IPoS, IPS and IAS, and firmly believes all civil services are created equal, but perceived differently because of various notions in society and culture. All services provide equal opportunity to keep the bureaucratic machine of the Indian Government running, which in turn is subservient to the will of the people.<\/strong>\n<\/div>\n\n\n<div style=\"background:var(--light-warm);border:1px solid var(--border);border-radius:8px;padding:28px 32px;margin:32px 0\">\n<h3 style=\"font-family:'Playfair Display',serif;color:var(--deep-rust);margin:0 0 16px;font-size:1.3em\">Index of Chapters<\/h3>\n<div style=\"display:grid;grid-template-columns:1fr 1fr;gap:6px 24px;font-size:.95em\">\n<a href=\"#methodology\" style=\"padding:6px 0;border-bottom:none;color:var(--ink);display:flex;gap:8px\"><span style=\"color:var(--amber);font-family:'DM Mono',monospace;font-size:.85em;min-width:24px\">\u00a7<\/span> Assumptions and Methodology<\/a>\n<a href=\"#ch5\" style=\"padding:6px 0;border-bottom:none;color:var(--ink);display:flex;gap:8px\"><span style=\"color:var(--amber);font-family:'DM Mono',monospace;font-size:.85em;min-width:24px\">5<\/span> UPSC CSE 2026 Notification \u2014 Restricting Re-Attempts<\/a>\n<a href=\"#ch1\" style=\"padding:6px 0;border-bottom:none;color:var(--ink);display:flex;gap:8px\"><span style=\"color:var(--amber);font-family:'DM Mono',monospace;font-size:.85em;min-width:24px\">1<\/span> The Examination Funnel \u2014 Apply, Write, Get Selected<\/a>\n<a href=\"#ch6\" style=\"padding:6px 0;border-bottom:none;color:var(--ink);display:flex;gap:8px\"><span style=\"color:var(--amber);font-family:'DM Mono',monospace;font-size:.85em;min-width:24px\">6<\/span> Economics of Repetition \u2014 Opportunity Costs & Superannuation<\/a>\n<a href=\"#ch2\" style=\"padding:6px 0;border-bottom:none;color:var(--ink);display:flex;gap:8px\"><span style=\"color:var(--amber);font-family:'DM Mono',monospace;font-size:.85em;min-width:24px\">2<\/span> The “Selected at Least Once” Phenomenon<\/a>\n<a href=\"#ch7\" style=\"padding:6px 0;border-bottom:none;color:var(--ink);display:flex;gap:8px\"><span style=\"color:var(--amber);font-family:'DM Mono',monospace;font-size:.85em;min-width:24px\">7<\/span> Why Give Your Best Shot \u2014 The Repeated First Attempt<\/a>\n<a href=\"#ch3\" style=\"padding:6px 0;border-bottom:none;color:var(--ink);display:flex;gap:8px\"><span style=\"color:var(--amber);font-family:'DM Mono',monospace;font-size:.85em;min-width:24px\">3<\/span> Adjacent-Year Re-Selection \u2014 Immediate Return Cycle<\/a>\n<a href=\"#\" style=\"padding:6px 0;border-bottom:none;color:transparent;pointer-events:none\"> <\/a>\n<a href=\"#ch4\" style=\"padding:6px 0;border-bottom:none;color:var(--ink);display:flex;gap:8px\"><span style=\"color:var(--amber);font-family:'DM Mono',monospace;font-size:.85em;min-width:24px\">4<\/span> Service Selection Probability \u2014 FTS vs. SAO<\/a>\n<\/div>\n<p style=\"font-size:.82em;color:var(--warm-gray);margin:14px 0 0;font-style:italic\">\u00a7 3.4 covers adjacent-year (Y\u2192Y+1) transitions only | \u00a7 4.3 covers lifetime first-to-last trajectories across the full 2020\u20132024 window<\/p>\n<\/div>\n\n\n<h2 id=\"methodology\">Assumptions and Methodology<\/h2>\n<div class=\"method-box\">\n<ol>\n<li><strong>Name-based matching<\/strong>: Candidates appearing across multiple years are identified by matching cleaned, standardised names (uppercase, special characters removed, whitespace collapsed). Minor spelling variations may cause missed matches (false negatives); common names may produce false positives.<\/li>\n<li><strong>Data cleaning<\/strong>: Two categories of data quality issues were identified and addressed:\n<br>\u2014 <strong>True duplicates<\/strong> (same name + same service appearing twice in the same year): 10 such rows removed.\n<br>\u2014 <strong>Ambiguous common names<\/strong> (same name with <em>different<\/em> services in the same year \u2014 different individuals): 33 such names excluded from all cross-year matching.<\/li>\n<li><strong>Reference year vs. analysis years<\/strong>: <strong>CSE 2020<\/strong> (673 usable candidates) is used solely as a <strong>reference year<\/strong>. The 2020 cohort is <strong>not<\/strong> itself analysed. All analysis covers <strong>CSE 2021, 2022, 2023, and 2024<\/strong>.<\/li>\n<li><strong>“Selected at Least Once” (SAO)<\/strong>: Candidates whose names also appear in any prior year’s allocation list (2020 onward).<\/li>\n<li><strong>“First-Time Selectees”<\/strong>: Names that do NOT appear in any prior year’s list. They may not be first-time exam takers \u2014 only first-time selectees within our detection range.<\/li>\n<li><strong>“Adjacent-year re-selector”<\/strong>: Selected in year Y and also in Y+1 \u2014 actual name-matching.<\/li>\n<li><strong>Aggregate statistics<\/strong> from PIB press releases and UPSC annual reports; approximate where exact figures unavailable.<\/li>\n<li><strong>No category or reservation data<\/strong> used. All figures are all-category aggregates.<\/li>\n<li><strong>Service grouping<\/strong>: IAS, IFS, IPS, and “Other Central Services” (IRS-IT, IRS-C&IT, IRMS, IDAS, IA&AS, ICLS, IIS, IPoS, DANICS, DANIPS, IDES, ITS, IRPFS, IP&TAFS, ICAS, AFHQ, PONDICS, etc.).<\/li>\n<li><strong>Service hierarchy<\/strong>: IAS > IFS > IPS > Other Central Services.<\/li>\n<li><strong>Financial calculations<\/strong> use the 7th CPC pay matrix and standard investment return assumptions.<\/li>\n<\/ol>\n<\/div>\n\n\n<h3>Data Cleaning Summary<\/h3>\n<table>\n<thead><tr><th>Year<\/th><th>Raw Records<\/th><th>Dups Removed<\/th><th>Clean<\/th><th>Ambiguous Flagged<\/th><th>Usable<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>2020<\/td><td class=\"num\">688<\/td><td class=\"num\">2<\/td><td class=\"num\">686<\/td><td class=\"num\">13<\/td><td class=\"num\">673<\/td><\/tr>\n<tr><td>2021<\/td><td class=\"num\">659<\/td><td class=\"num\">2<\/td><td class=\"num\">657<\/td><td class=\"num\">14<\/td><td class=\"num\">643<\/td><\/tr>\n<tr><td>2022<\/td><td class=\"num\">784<\/td><td class=\"num\">3<\/td><td class=\"num\">781<\/td><td class=\"num\">14<\/td><td class=\"num\">767<\/td><\/tr>\n<tr><td>2023<\/td><td class=\"num\">995<\/td><td class=\"num\">1<\/td><td class=\"num\">994<\/td><td class=\"num\">39<\/td><td class=\"num\">955<\/td><\/tr>\n<tr><td>2024<\/td><td class=\"num\">965<\/td><td class=\"num\">2<\/td><td class=\"num\">963<\/td><td class=\"num\">25<\/td><td class=\"num\">938<\/td><\/tr>\n<tr><td><strong>Total<\/strong><\/td><td class=\"num\"><strong>4,091<\/strong><\/td><td class=\"num\"><strong>10<\/strong><\/td><td class=\"num\"><strong>4,081<\/strong><\/td><td class=\"num\"><strong>\u2014<\/strong><\/td><td class=\"num\"><strong>3,976<\/strong><\/td><\/tr>\n<\/tbody>\n<\/table>\n<p>33 ambiguous names (common names like ASHISH KUMAR, SANDEEP KUMAR, NIDHI, etc. appearing with different services in the same year) were excluded from all cross-year matching. Full list documented in the accompanying Excel workbook.<\/p>\n\n<div class=\"separator\">\u2022 \u2022 \u2022<\/div>\n\n\n<h2 id=\"ch1\"><span class=\"chapter-label\">Chapter One<\/span>The Examination Funnel \u2014 How Many Apply, Write, and Get Selected?<\/h2>\n\n<h3>1.1 Year-Wise Examination Statistics<\/h3>\n<table>\n<thead><tr><th>Year<\/th><th>Applied (Approx.)<\/th><th>Appeared Prelims<\/th><th>Qualified Mains<\/th><th>Interviewed<\/th><th>Finally Selected<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>2020<\/td><td class=\"num\">~10,58,000<\/td><td class=\"num\">~4,82,000<\/td><td class=\"num\">~10,564<\/td><td class=\"num\">~2,100<\/td><td class=\"num\">761<\/td><\/tr>\n<tr><td>2021<\/td><td class=\"num\">~10,93,984<\/td><td class=\"num\">~5,09,113<\/td><td class=\"num\">~10,000<\/td><td class=\"num\">~2,080<\/td><td class=\"num\">712<\/td><\/tr>\n<tr><td>2022<\/td><td class=\"num\">~11,52,566<\/td><td class=\"num\">~5,73,735<\/td><td class=\"num\">~13,090<\/td><td class=\"num\">~2,529<\/td><td class=\"num\">933<\/td><\/tr>\n<tr><td>2023<\/td><td class=\"num\">~13,35,697<\/td><td class=\"num\">~6,50,000<\/td><td class=\"num\">~14,624<\/td><td class=\"num\">~2,916<\/td><td class=\"num\">1,016<\/td><\/tr>\n<tr><td>2024<\/td><td class=\"num\">~9,92,599<\/td><td class=\"num\">~5,83,213<\/td><td class=\"num\">~14,627<\/td><td class=\"num\">~2,845<\/td><td class=\"num\">1,009<\/td><\/tr>\n<\/tbody>\n<\/table>\n<p style=\"font-size:.85em;color:var(--warm-gray);font-style:italic\">Sources: PIB press releases, UPSC Annual Reports.<\/p>\n\n<h3>1.2 Stage-Wise Elimination Probabilities<\/h3>\n\n\n<div class=\"funnel\">\n<div class=\"funnel-step\" style=\"width:90%;background:var(--tbl-hdr)\">~10.9 Lakh Applied<span class=\"detail\">Average across 2020\u20132024<\/span><\/div>\n<div class=\"funnel-arrow\">\u25bc ~50\u201355% appearance rate<\/div>\n<div class=\"funnel-step\" style=\"width:72%;background:var(--deep-rust)\">~5.8 Lakh Appeared for Prelims<\/div>\n<div class=\"funnel-arrow\">\u25bc ~1.5\u20132.5% qualification rate<\/div>\n<div class=\"funnel-step\" style=\"width:38%;background:var(--rust)\">~14,000 Qualified for Mains<\/div>\n<div class=\"funnel-arrow\">\u25bc ~19\u201322% interview rate<\/div>\n<div class=\"funnel-step\" style=\"width:22%;background:var(--amber)\">~2,800 Called for Interview<\/div>\n<div class=\"funnel-arrow\">\u25bc ~33\u201340% selection rate<\/div>\n<div class=\"funnel-step\" style=\"width:14%;background:var(--sage)\">~1,000 Finally Selected<\/div>\n<\/div>\n\n<table>\n<thead><tr><th>Stage Transition<\/th><th>Approx. Probability<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>Applied \u2192 Appeared for Prelims<\/td><td class=\"pct\">~50\u201355%<\/td><\/tr>\n<tr><td>Appeared Prelims \u2192 Qualified for Mains<\/td><td class=\"pct\">~1.5\u20132.5%<\/td><\/tr>\n<tr><td>Qualified Mains \u2192 Called for Interview<\/td><td class=\"pct\">~19\u201322%<\/td><\/tr>\n<tr><td>Interviewed \u2192 Finally Selected<\/td><td class=\"pct\">~33\u201340%<\/td><\/tr>\n<tr><td><strong>Applied \u2192 Finally Selected<\/strong><\/td><td class=\"pct\"><strong>~0.07\u20130.10%<\/strong><\/td><\/tr>\n<tr><td><strong>Appeared Prelims \u2192 Finally Selected<\/strong><\/td><td class=\"pct\"><strong>~0.13\u20130.20%<\/strong><\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<p>The Preliminary Examination eliminates approximately 97\u201398% of candidates who appear. Once a candidate reaches the interview stage, the selection rate improves to roughly one-in-three \u2014 the Mains examination is the true differentiator.<\/p>\n\n<h3>1.3 Parsed Allocation Data<\/h3>\n<table>\n<thead><tr><th>Year<\/th><th>Role in This Analysis<\/th><th>Usable Candidates<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>2020<\/td><td><strong>Reference year<\/strong> (not analysed)<\/td><td class=\"num\">673<\/td><\/tr>\n<tr><td>2021<\/td><td>Analysis year<\/td><td class=\"num\">643<\/td><\/tr>\n<tr><td>2022<\/td><td>Analysis year<\/td><td class=\"num\">767<\/td><\/tr>\n<tr><td>2023<\/td><td>Analysis year<\/td><td class=\"num\">955<\/td><\/tr>\n<tr><td>2024<\/td><td>Analysis year<\/td><td class=\"num\">938<\/td><\/tr>\n<tr><td><strong>2021\u20132024 Total<\/strong><\/td><td>\u2014<\/td><td class=\"num\"><strong>3,303<\/strong><\/td><\/tr>\n<\/tbody>\n<\/table>\n<p>The 3,303 usable allocations across the four analysis years represent <strong>2,939 unique individuals<\/strong>. An additional 673 usable individuals in the 2020 reference year provide the baseline against which “Selected at Least Once” status is determined.<\/p>\n\n<div class=\"separator\">\u2022 \u2022 \u2022<\/div>\n\n\n<h2 id=\"ch2\"><span class=\"chapter-label\">Chapter Two<\/span>The “Selected at Least Once” Phenomenon \u2014 Repetition Across Years<\/h2>\n\n<h3>2.1 Year-Wise Composition: First-Time Selectees vs. Selected at Least Once<\/h3>\n<p>For each analysis year, a candidate is classified as “Selected at Least Once” (SAO) if their name appears in any prior year’s allocation list (starting from 2020). Only usable (non-ambiguous) names are classified.<\/p>\n\n<table>\n<thead><tr><th>Year<\/th><th>Total Selected<\/th><th>Usable<\/th><th>First-Time Selectees<\/th><th>SAO<\/th><th>% First-Time<\/th><th>% SAO<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>2021<\/td><td class=\"num\">657<\/td><td class=\"num\">643<\/td><td class=\"num\">586<\/td><td class=\"num\">57<\/td><td class=\"pct\">91.1%<\/td><td class=\"pct\">8.9%<\/td><\/tr>\n<tr><td>2022<\/td><td class=\"num\">781<\/td><td class=\"num\">767<\/td><td class=\"num\">666<\/td><td class=\"num\">101<\/td><td class=\"pct\">86.8%<\/td><td class=\"pct\">13.2%<\/td><\/tr>\n<tr><td>2023<\/td><td class=\"num\">994<\/td><td class=\"num\">955<\/td><td class=\"num\">808<\/td><td class=\"num\">147<\/td><td class=\"pct\">84.6%<\/td><td class=\"pct\">15.4%<\/td><\/tr>\n<tr><td>2024<\/td><td class=\"num\">963<\/td><td class=\"num\">938<\/td><td class=\"num\">743<\/td><td class=\"num\">195<\/td><td class=\"pct\">79.2%<\/td><td class=\"pct\"><strong>20.8%<\/strong><\/td><\/tr>\n<\/tbody>\n<\/table>\n\n\n<div class=\"chart-container\">\n<div class=\"chart-title\">SAO Proportion Growing Steadily (2021\u20132024)<\/div>\n<canvas id=\"saoTrendChart\" height=\"280\"><\/canvas>\n<div class=\"chart-note\">2021 SAO (8.9%) based on 1-year lookback; 2024 (20.8%) based on 4-year lookback \u2014 most reliable figure.<\/div>\n<\/div>\n\n<p>The proportion of SAO candidates has grown steadily from 8.9% in 2021 to <strong>20.8% in 2024<\/strong>. By 2024, approximately <strong>one in five usable selectees<\/strong> had already been selected in at least one prior year.<\/p>\n<p><em>Note: The 2021 SAO figure (8.9%) is based on only one year of lookback (2020). The true SAO proportion in 2021 is likely higher, as candidates selected before 2020 are invisible to our detection. The 2024 figure (20.8%), with four years of lookback, is the most complete and reliable.<\/em><\/p>\n\n<h3>2.2 Unique Candidate Summary (2021\u20132024)<\/h3>\n\n<div class=\"stat-grid\">\n<div class=\"stat-card\"><span class=\"big\">2,939<\/span><span class=\"label\">Unique Individuals (usable)<\/span><\/div>\n<div class=\"stat-card\"><span class=\"big\">456<\/span><span class=\"label\">Selected at Least Once (15.5%)<\/span><\/div>\n<div class=\"stat-card\"><span class=\"big\">2,483<\/span><span class=\"label\">First-Time Selectees (84.5%)<\/span><\/div>\n<div class=\"stat-card\"><span class=\"big\">364<\/span><span class=\"label\">Re-selection Instances<\/span><\/div>\n<\/div>\n\n<table>\n<thead><tr><th>Metric<\/th><th>Count<\/th><th>%<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>Total unique individuals in 2021\u20132024 (usable)<\/td><td class=\"num\">2,939<\/td><td class=\"pct\">100%<\/td><\/tr>\n<tr><td>Of these, also appeared in 2020 reference year<\/td><td class=\"num\">136<\/td><td class=\"pct\">4.6%<\/td><\/tr>\n<tr><td>Multi-selected within 2021\u20132024 (appeared 2+ times)<\/td><td class=\"num\">344<\/td><td class=\"pct\">11.7%<\/td><\/tr>\n<tr><td>Total “Selected at Least Once” unique individuals<\/td><td class=\"num\">456<\/td><td class=\"pct\">15.5%<\/td><\/tr>\n<tr><td>Purely first-time selectee individuals<\/td><td class=\"num\">2,483<\/td><td class=\"pct\">84.5%<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<h3>2.3 Frequency of Re-Selection (Within 2021\u20132024)<\/h3>\n\n<div class=\"chart-container\" style=\"max-width:500px\">\n<div class=\"chart-title\">Selection Frequency Distribution<\/div>\n<canvas id=\"freqChart\" height=\"250\"><\/canvas>\n<\/div>\n\n<table>\n<thead><tr><th>Times Selected in 2021\u20132024<\/th><th>Candidates<\/th><th>%<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>1 time<\/td><td class=\"num\">2,595<\/td><td class=\"pct\">88.3%<\/td><\/tr>\n<tr><td>2 times<\/td><td class=\"num\">326<\/td><td class=\"pct\">11.1%<\/td><\/tr>\n<tr><td>3 times<\/td><td class=\"num\">16<\/td><td class=\"pct\">0.5%<\/td><\/tr>\n<tr><td>4 times (all four years)<\/td><td class=\"num\">2<\/td><td class=\"pct\">0.1%<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<p>Total re-selection instances (usable allocations minus unique individuals) = <strong>364<\/strong> across the four analysis years. These 364 “seat-opportunities” were consumed by candidates who had already been allocated a service at least once before.<\/p>\n\n<h3>2.4 Year-Pair Overlap Matrix (Usable Names Only)<\/h3>\n\n<div class=\"chart-container\">\n<div class=\"chart-title\">Cross-Year Overlap \u2014 Candidates Appearing in Both Years<\/div>\n<canvas id=\"overlapChart\" height=\"280\"><\/canvas>\n<div class=\"chart-note\">Adjacent years show highest overlap; diminishes with distance as candidates exit the cycle.<\/div>\n<\/div>\n\n<table>\n<thead><tr><th><\/th><th>2020<\/th><th>2021<\/th><th>2022<\/th><th>2023<\/th><th>2024<\/th><\/tr><\/thead>\n<tbody>\n<tr><td><strong>2020<\/strong><\/td><td class=\"num\">673<\/td><td class=\"num\">57<\/td><td class=\"num\">49<\/td><td class=\"num\">29<\/td><td class=\"num\">25<\/td><\/tr>\n<tr><td><strong>2021<\/strong><\/td><td class=\"num\">57<\/td><td class=\"num\">643<\/td><td class=\"num\">56<\/td><td class=\"num\">47<\/td><td class=\"num\">21<\/td><\/tr>\n<tr><td><strong>2022<\/strong><\/td><td class=\"num\">49<\/td><td class=\"num\">56<\/td><td class=\"num\">767<\/td><td class=\"num\">87<\/td><td class=\"num\">73<\/td><\/tr>\n<tr><td><strong>2023<\/strong><\/td><td class=\"num\">29<\/td><td class=\"num\">47<\/td><td class=\"num\">87<\/td><td class=\"num\">955<\/td><td class=\"num\">102<\/td><\/tr>\n<tr><td><strong>2024<\/strong><\/td><td class=\"num\">25<\/td><td class=\"num\">21<\/td><td class=\"num\">73<\/td><td class=\"num\">102<\/td><td class=\"num\">938<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<h3>2.5 Implications<\/h3>\n\n<div class=\"callout\">\nFor every 1,000 usable seats in 2024, approximately <strong>208 were taken by returning selectees<\/strong>, leaving roughly <strong>792 for new entrants<\/strong>. Across the four analysis years, <strong>364 seat-opportunities<\/strong> were consumed by re-selection.\n<\/div>\n\n<div class=\"separator\">\u2022 \u2022 \u2022<\/div>\n\n\n<h2 id=\"ch3\"><span class=\"chapter-label\">Chapter Three<\/span>Adjacent-Year Re-Selection \u2014 The Immediate Return Cycle and Service Improvement Probability<\/h2>\n\n<p>This chapter examines candidates selected in year Y who re-appear in year Y+1 \u2014 the most consequential form of re-attempting. All figures are from actual name-matching on usable (non-ambiguous) names only.<\/p>\n\n<h3>3.1 Adjacent-Year Re-Selection Rates<\/h3>\n<table>\n<thead><tr><th>Year Pair<\/th><th>Usable Y1<\/th><th>Usable Y2<\/th><th>Overlap<\/th><th>Re-Sel Rate (% Y1)<\/th><th>% Y2 Seats<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>2020 \u2192 2021<\/td><td class=\"num\">673<\/td><td class=\"num\">643<\/td><td class=\"num\">57<\/td><td class=\"pct\">8.5%<\/td><td class=\"pct\">8.9%<\/td><\/tr>\n<tr><td>2021 \u2192 2022<\/td><td class=\"num\">643<\/td><td class=\"num\">767<\/td><td class=\"num\">56<\/td><td class=\"pct\">8.7%<\/td><td class=\"pct\">7.3%<\/td><\/tr>\n<tr><td>2022 \u2192 2023<\/td><td class=\"num\">767<\/td><td class=\"num\">955<\/td><td class=\"num\">87<\/td><td class=\"pct\">11.3%<\/td><td class=\"pct\">9.1%<\/td><\/tr>\n<tr><td>2023 \u2192 2024<\/td><td class=\"num\">955<\/td><td class=\"num\">938<\/td><td class=\"num\">102<\/td><td class=\"pct\">10.7%<\/td><td class=\"pct\">10.9%<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<p>Approximately <strong>8.5\u201311.3% of each year’s selectees<\/strong> re-appear in the very next cycle, consuming <strong>7.3\u201310.9% of the next year’s seats<\/strong>. The rate has been trending upward.<\/p>\n\n<h3>3.2 Where Do Adjacent-Year Re-Selectors Come From?<\/h3>\n\n<div class=\"chart-container\">\n<div class=\"chart-title\">Prior Service of Adjacent-Year Re-Selectors<\/div>\n<canvas id=\"feederChart\" height=\"260\"><\/canvas>\n<div class=\"chart-note\">~66\u201376% consistently from Central Services; ~19\u201332% from IPS<\/div>\n<\/div>\n\n<table>\n<thead><tr><th>Year Pair<\/th><th>From Other Central Services<\/th><th>From IPS<\/th><th>From IAS<\/th><th>From IFS<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>2020 \u2192 2021<\/td><td class=\"num\">40 (70.2%)<\/td><td class=\"num\">13 (22.8%)<\/td><td class=\"num\">3 (5.3%)<\/td><td class=\"num\">1 (1.8%)<\/td><\/tr>\n<tr><td>2021 \u2192 2022<\/td><td class=\"num\">37 (66.1%)<\/td><td class=\"num\">18 (32.1%)<\/td><td class=\"num\">1 (1.8%)<\/td><td class=\"num\">0 (0.0%)<\/td><\/tr>\n<tr><td>2022 \u2192 2023<\/td><td class=\"num\">63 (72.4%)<\/td><td class=\"num\">17 (19.5%)<\/td><td class=\"num\">7 (8.0%)<\/td><td class=\"num\">0 (0.0%)<\/td><\/tr>\n<tr><td>2023 \u2192 2024<\/td><td class=\"num\">77 (75.5%)<\/td><td class=\"num\">21 (20.6%)<\/td><td class=\"num\">3 (2.9%)<\/td><td class=\"num\">1 (1.0%)<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<h3>3.3 Service Improvement Probability<\/h3>\n\n<div class=\"chart-container\">\n<div class=\"chart-title\">Outcome of Adjacent-Year Re-Selection: Did They Upgrade?<\/div>\n<canvas id=\"upgradeChart\" height=\"260\"><\/canvas>\n<\/div>\n\n<table>\n<thead><tr><th>Year Pair<\/th><th>Re-Selected<\/th><th>Upgraded<\/th><th>Same Tier<\/th><th>Different Tier<\/th><th>Upgrade Rate<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>2020 \u2192 2021<\/td><td class=\"num\">57<\/td><td class=\"num\">39<\/td><td class=\"num\">12<\/td><td class=\"num\">6<\/td><td class=\"pct\"><strong>68.4%<\/strong><\/td><\/tr>\n<tr><td>2021 \u2192 2022<\/td><td class=\"num\">56<\/td><td class=\"num\">33<\/td><td class=\"num\">17<\/td><td class=\"num\">6<\/td><td class=\"pct\"><strong>58.9%<\/strong><\/td><\/tr>\n<tr><td>2022 \u2192 2023<\/td><td class=\"num\">87<\/td><td class=\"num\">50<\/td><td class=\"num\">27<\/td><td class=\"num\">10<\/td><td class=\"pct\"><strong>57.5%<\/strong><\/td><\/tr>\n<tr><td>2023 \u2192 2024<\/td><td class=\"num\">102<\/td><td class=\"num\">64<\/td><td class=\"num\">31<\/td><td class=\"num\">7<\/td><td class=\"pct\"><strong>62.7%<\/strong><\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<p><strong>~58\u201368% of adjacent-year re-selectors achieve a service upgrade.<\/strong> But ~21\u201331% remain in the same tier, and ~7\u201311% move to a different tier in the opposite direction.<\/p>\n\n<h3>3.4 Service Transitions in the Immediate Next Year \u2014 Aggregated Across All Four Adjacent Pairs<\/h3>\n\n<p>The table below shows where candidates moved when re-selected <strong>in the very next examination cycle (Y \u2192 Y+1 only)<\/strong>. This captures only the immediate one-year return pattern.<\/p>\n\n<div class=\"chart-container\">\n<div class=\"chart-title\">Adjacent-Year Service Transitions Only (Y \u2192 Y+1, All Four Pairs Combined)<\/div>\n<canvas id=\"transChart\" height=\"320\"><\/canvas>\n<\/div>\n\n<table>\n<thead><tr><th>Transition (Y \u2192 Y+1)<\/th><th>Count<\/th><th>Direction<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>Other Central Services \u2192 Other Central Services<\/td><td class=\"num\">76<\/td><td>\u2192 Same tier<\/td><\/tr>\n<tr><td>Other Central Services \u2192 IAS<\/td><td class=\"num\">68<\/td><td>\u2191 Upgrade<\/td><\/tr>\n<tr><td>Other Central Services \u2192 IPS<\/td><td class=\"num\">61<\/td><td>\u2191 Upgrade<\/td><\/tr>\n<tr><td>IPS \u2192 IAS<\/td><td class=\"num\">36<\/td><td>\u2191 Upgrade<\/td><\/tr>\n<tr><td>IPS \u2192 Other Central Services<\/td><td class=\"num\">19<\/td><td>\u2193 Different tier<\/td><\/tr>\n<tr><td>Other Central Services \u2192 IFS<\/td><td class=\"num\">12<\/td><td>\u2191 Upgrade<\/td><\/tr>\n<tr><td>IPS \u2192 IFS<\/td><td class=\"num\">8<\/td><td>\u2191 Upgrade<\/td><\/tr>\n<tr><td>IPS \u2192 IPS<\/td><td class=\"num\">6<\/td><td>\u2192 Same tier<\/td><\/tr>\n<tr><td>IAS \u2192 Other Central Services<\/td><td class=\"num\">6<\/td><td>\u2193 Different tier<\/td><\/tr>\n<tr><td>IAS \u2192 IAS<\/td><td class=\"num\">5<\/td><td>\u2192 Same tier<\/td><\/tr>\n<tr><td>IAS \u2192 IPS<\/td><td class=\"num\">3<\/td><td>\u2192 Mixed<\/td><\/tr>\n<tr><td>IFS \u2192 IAS<\/td><td class=\"num\">1<\/td><td>\u2191 Upgrade<\/td><\/tr>\n<tr><td>IFS \u2192 IPS<\/td><td class=\"num\">1<\/td><td>\u2192 Mixed<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<p>The most frequent transition pathways: <strong>Central Services \u2192 IAS<\/strong> (68), <strong>Central Services \u2192 IPS<\/strong> (61), <strong>IPS \u2192 IAS<\/strong> (36) \u2014 accounting for 165 of 186 total service changes to a higher-ranked group.<\/p>\n\n<h3>3.5 IAS Selection Rate Among Re-Selectors<\/h3>\n<table>\n<thead><tr><th>Year Pair<\/th><th>Re-Selectors<\/th><th>Selected into IAS<\/th><th>IAS Selection Rate<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>2020 \u2192 2021<\/td><td class=\"num\">57<\/td><td class=\"num\">24<\/td><td class=\"pct\"><strong>42.1%<\/strong><\/td><\/tr>\n<tr><td>2021 \u2192 2022<\/td><td class=\"num\">56<\/td><td class=\"num\">21<\/td><td class=\"pct\"><strong>37.5%<\/strong><\/td><\/tr>\n<tr><td>2022 \u2192 2023<\/td><td class=\"num\">87<\/td><td class=\"num\">29<\/td><td class=\"pct\"><strong>33.3%<\/strong><\/td><\/tr>\n<tr><td>2023 \u2192 2024<\/td><td class=\"num\">102<\/td><td class=\"num\">36<\/td><td class=\"pct\"><strong>35.3%<\/strong><\/td><\/tr>\n<\/tbody>\n<\/table>\n<p><strong>One-third to two-fifths<\/strong> of adjacent-year re-selectors are allocated IAS in their subsequent selection \u2014 a proportion notably higher than the ~18% share IAS represents in the overall allocation.<\/p>\n\n<h3>3.6 The Non-Adjacent Gap: Skipping a Year<\/h3>\n<table>\n<thead><tr><th>Gap Pair<\/th><th>Total Overlap<\/th><th>Skipped Middle Year<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>2020 \u2192 2022 (skipped 2021)<\/td><td class=\"num\">49<\/td><td class=\"num\">45<\/td><\/tr>\n<tr><td>2021 \u2192 2023 (skipped 2022)<\/td><td class=\"num\">47<\/td><td class=\"num\">41<\/td><\/tr>\n<tr><td>2022 \u2192 2024 (skipped 2023)<\/td><td class=\"num\">73<\/td><td class=\"num\">62<\/td><\/tr>\n<\/tbody>\n<\/table>\n<p>Substantial numbers skip a year and return \u2014 the re-attempt cycle is a persistent, multi-year phenomenon.<\/p>\n\n<h3>3.7 Summary<\/h3>\n<div class=\"stat-grid\">\n<div class=\"stat-card\"><span class=\"big\">8.5\u201311.3%<\/span><span class=\"label\">of selectees re-appear next cycle<\/span><\/div>\n<div class=\"stat-card\"><span class=\"big\">~70%<\/span><span class=\"label\">come from Central Services<\/span><\/div>\n<div class=\"stat-card\"><span class=\"big\">~62%<\/span><span class=\"label\">achieve service upgrade<\/span><\/div>\n<div class=\"stat-card\"><span class=\"big\">~36%<\/span><span class=\"label\">are allocated IAS<\/span><\/div>\n<\/div>\n\n<div class=\"separator\">\u2022 \u2022 \u2022<\/div>\n\n\n<h2 id=\"ch4\"><span class=\"chapter-label\">Chapter Four<\/span>Service Selection Probability \u2014 First-Time Selectees vs. Selected at Least Once<\/h2>\n\n<h3>4.1 Service-Wise Breakdown by Year<\/h3>\n\n<h4>CSE 2021<\/h4>\n<table>\n<thead><tr><th>Service Group<\/th><th>Usable<\/th><th>First-Time Selectees<\/th><th>SAO<\/th><th>% First-Time<\/th><th>% SAO<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>IAS<\/td><td class=\"num\">175<\/td><td class=\"num\">151<\/td><td class=\"num\">24<\/td><td class=\"pct\">86.3%<\/td><td class=\"pct\">13.7%<\/td><\/tr>\n<tr><td>IFS<\/td><td class=\"num\">36<\/td><td class=\"num\">33<\/td><td class=\"num\">3<\/td><td class=\"pct\">91.7%<\/td><td class=\"pct\">8.3%<\/td><\/tr>\n<tr><td>IPS<\/td><td class=\"num\">197<\/td><td class=\"num\">179<\/td><td class=\"num\">18<\/td><td class=\"pct\">90.9%<\/td><td class=\"pct\">9.1%<\/td><\/tr>\n<tr><td>Other Central Services<\/td><td class=\"num\">235<\/td><td class=\"num\">223<\/td><td class=\"num\">12<\/td><td class=\"pct\">94.9%<\/td><td class=\"pct\">5.1%<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<h4>CSE 2022<\/h4>\n<table>\n<thead><tr><th>Service Group<\/th><th>Usable<\/th><th>First-Time Selectees<\/th><th>SAO<\/th><th>% First-Time<\/th><th>% SAO<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>IAS<\/td><td class=\"num\">157<\/td><td class=\"num\">122<\/td><td class=\"num\">35<\/td><td class=\"pct\">77.7%<\/td><td class=\"pct\">22.3%<\/td><\/tr>\n<tr><td>IFS<\/td><td class=\"num\">29<\/td><td class=\"num\">25<\/td><td class=\"num\">4<\/td><td class=\"pct\">86.2%<\/td><td class=\"pct\">13.8%<\/td><\/tr>\n<tr><td>IPS<\/td><td class=\"num\">170<\/td><td class=\"num\">148<\/td><td class=\"num\">22<\/td><td class=\"pct\">87.1%<\/td><td class=\"pct\">12.9%<\/td><\/tr>\n<tr><td>Other Central Services<\/td><td class=\"num\">411<\/td><td class=\"num\">371<\/td><td class=\"num\">40<\/td><td class=\"pct\">90.3%<\/td><td class=\"pct\">9.7%<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<h4>CSE 2023<\/h4>\n<table>\n<thead><tr><th>Service Group<\/th><th>Usable<\/th><th>First-Time Selectees<\/th><th>SAO<\/th><th>% First-Time<\/th><th>% SAO<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>IAS<\/td><td class=\"num\">174<\/td><td class=\"num\">128<\/td><td class=\"num\">46<\/td><td class=\"pct\">73.6%<\/td><td class=\"pct\">26.4%<\/td><\/tr>\n<tr><td>IFS<\/td><td class=\"num\">36<\/td><td class=\"num\">28<\/td><td class=\"num\">8<\/td><td class=\"pct\">77.8%<\/td><td class=\"pct\">22.2%<\/td><\/tr>\n<tr><td>IPS<\/td><td class=\"num\">190<\/td><td class=\"num\">157<\/td><td class=\"num\">33<\/td><td class=\"pct\">82.6%<\/td><td class=\"pct\">17.4%<\/td><\/tr>\n<tr><td>Other Central Services<\/td><td class=\"num\">555<\/td><td class=\"num\">495<\/td><td class=\"num\">60<\/td><td class=\"pct\">89.2%<\/td><td class=\"pct\">10.8%<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<h4>CSE 2024<\/h4>\n<table>\n<thead><tr><th>Service Group<\/th><th>Usable<\/th><th>First-Time Selectees<\/th><th>SAO<\/th><th>% First-Time<\/th><th>% SAO<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>IAS<\/td><td class=\"num\">170<\/td><td class=\"num\">106<\/td><td class=\"num\">64<\/td><td class=\"pct\">62.4%<\/td><td class=\"pct\"><strong>37.6%<\/strong><\/td><\/tr>\n<tr><td>IFS<\/td><td class=\"num\">52<\/td><td class=\"num\">37<\/td><td class=\"num\">15<\/td><td class=\"pct\">71.2%<\/td><td class=\"pct\"><strong>28.8%<\/strong><\/td><\/tr>\n<tr><td>IPS<\/td><td class=\"num\">145<\/td><td class=\"num\">104<\/td><td class=\"num\">41<\/td><td class=\"pct\">71.7%<\/td><td class=\"pct\"><strong>28.3%<\/strong><\/td><\/tr>\n<tr><td>Other Central Services<\/td><td class=\"num\">571<\/td><td class=\"num\">496<\/td><td class=\"num\">75<\/td><td class=\"pct\">86.9%<\/td><td class=\"pct\">13.1%<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<h3>4.2 Proportion of SAO Candidates in IAS Over Time<\/h3>\n\n<div class=\"chart-container\">\n<div class=\"chart-title\">SAO Proportion by Service Group (2021\u20132024)<\/div>\n<canvas id=\"svcSaoChart\" height=\"280\"><\/canvas>\n<\/div>\n\n<table>\n<thead><tr><th>Year<\/th><th>IAS Usable<\/th><th>SAO in IAS<\/th><th>% SAO<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>2021<\/td><td class=\"num\">175<\/td><td class=\"num\">24<\/td><td class=\"pct\">13.7%<\/td><\/tr>\n<tr><td>2022<\/td><td class=\"num\">157<\/td><td class=\"num\">35<\/td><td class=\"pct\">22.3%<\/td><\/tr>\n<tr><td>2023<\/td><td class=\"num\">174<\/td><td class=\"num\">46<\/td><td class=\"pct\">26.4%<\/td><\/tr>\n<tr><td>2024<\/td><td class=\"num\">170<\/td><td class=\"num\">64<\/td><td class=\"pct\"><strong>37.6%<\/strong><\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<p>By 2024, nearly <strong>four out of every ten IAS seats<\/strong> (among usable names) went to candidates who had been selected in a prior year. The steady acceleration from 13.7% to 37.6% over four years is consistent.<\/p>\n\n<h3>4.3 Lifetime Service Trajectory of All 456 SAO Candidates \u2014 First Selection to Most Recent (Full 2020\u20132024 Window)<\/h3>\n<p>Unlike Section 3.4 (which tracked only adjacent-year Y \u2192 Y+1 transitions), this section traces each SAO candidate’s <strong>entire journey from their first-ever selection to their most recent selection<\/strong> across the full five-year window. A candidate selected in 2020, 2022, and 2024 is represented here as a single trajectory from their 2020 service to their 2024 service \u2014 regardless of what happened in between.<\/p>\n<p>Among the 456 SAO candidates (usable, 2+ selections, present in 2021\u20132024):<\/p>\n\n<table>\n<thead><tr><th>First Service \u2192 Most Recent Service<\/th><th>Count<\/th><th>Interpretation<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>Other Central Services \u2192 Other Central Services<\/td><td class=\"num\">119<\/td><td>Same tier<\/td><\/tr>\n<tr><td>Other Central Services \u2192 IAS<\/td><td class=\"num\">106<\/td><td>Moved to IAS<\/td><\/tr>\n<tr><td>Other Central Services \u2192 IPS<\/td><td class=\"num\">85<\/td><td>Moved to IPS<\/td><\/tr>\n<tr><td>IPS \u2192 IAS<\/td><td class=\"num\">50<\/td><td>Moved from IPS to IAS<\/td><\/tr>\n<tr><td>IPS \u2192 Other Central Services<\/td><td class=\"num\">32<\/td><td>Cadre\/rank preference<\/td><\/tr>\n<tr><td>Other Central Services \u2192 IFS<\/td><td class=\"num\">20<\/td><td>Moved to IFS<\/td><\/tr>\n<tr><td>IAS \u2192 Other Central Services<\/td><td class=\"num\">11<\/td><td>Name-matching noise likely<\/td><\/tr>\n<tr><td>IPS \u2192 IFS<\/td><td class=\"num\">10<\/td><td>Moved from IPS to IFS<\/td><\/tr>\n<tr><td>IAS \u2192 IPS<\/td><td class=\"num\">8<\/td><td>Lateral<\/td><\/tr>\n<tr><td>IPS \u2192 IPS<\/td><td class=\"num\">6<\/td><td>Same service<\/td><\/tr>\n<tr><td>IAS \u2192 IAS<\/td><td class=\"num\">6<\/td><td>Same<\/td><\/tr>\n<tr><td>IFS \u2192 various<\/td><td class=\"num\">3<\/td><td>Very rare<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<div class=\"chart-container\">\n<div class=\"chart-title\">Overall Trajectory Outcomes \u2014 456 SAO Candidates<\/div>\n<canvas id=\"trajChart\" height=\"250\"><\/canvas>\n<\/div>\n\n<table>\n<thead><tr><th>Outcome<\/th><th>Count<\/th><th>% of All SAO<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>Upgraded service<\/td><td class=\"num\">272<\/td><td class=\"pct\">59.6%<\/td><\/tr>\n<tr><td>Same service tier<\/td><td class=\"num\">131<\/td><td class=\"pct\">28.7%<\/td><\/tr>\n<tr><td>Moved to different tier<\/td><td class=\"num\">53<\/td><td class=\"pct\">11.6%<\/td><\/tr>\n<tr><td><strong>Final service = IAS<\/strong><\/td><td class=\"num\"><strong>163<\/strong><\/td><td class=\"pct\"><strong>35.7%<\/strong><\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<p>163 of 456 SAO candidates (35.7%) ultimately ended up in IAS. This means that nearly <strong>two-thirds of SAO candidates did not achieve the IAS allocation<\/strong> despite being selected multiple times.<\/p>\n\n<h3>4.4 What This Means for a First-Time Selectee Targeting IAS<\/h3>\n<div class=\"callout\">\nA first-time selectee targeting IAS in 2024 is competing for approximately <strong>106 first-time selectee IAS seats<\/strong> out of 170 usable total \u2014 the remaining 64 were taken by SAO candidates. The effective competition for first-time selectee IAS seats is substantially more intense than the headline numbers suggest.\n<\/div>\n\n<div class=\"separator\">\u2022 \u2022 \u2022<\/div>\n\n\n<h2 id=\"ch5\"><span class=\"chapter-label\">Chapter Five<\/span>The UPSC CSE 2026 Notification \u2014 Restricting Re-Attempts by Serving Officers<\/h2>\n\n<h3>5.1 What Changed<\/h3>\n<p>The UPSC CSE 2026 notification (February 4, 2026) introduced landmark changes:<\/p>\n\n<div class=\"compare-grid\">\n<div class=\"compare-card\">\n<h4>Pre-2026 Rules<\/h4>\n<p><strong>IAS\/IFS officers<\/strong>: Permitted to attempt exam while serving.<\/p>\n<p><strong>IPS officers<\/strong>: Permitted to attempt and opt for IPS again.<\/p>\n<p><strong>Central Services<\/strong>: Unlimited attempts within age\/attempt limits.<\/p>\n<\/div>\n<div class=\"compare-card\" style=\"border-color:var(--deep-rust)\">\n<h4>Post-2026 Rules<\/h4>\n<p><strong>IAS\/IFS officers<\/strong>: Completely barred. Resignation mandatory.<\/p>\n<p><strong>IPS officers<\/strong>: Can attempt, but cannot be allocated IPS again.<\/p>\n<p><strong>Central Services<\/strong>: One-time improvement window only. Non-repeatable.<\/p>\n<p><strong>2028 cutoff<\/strong>: Resignation mandatory for any serving officer to re-attempt.<\/p>\n<\/div>\n<\/div>\n\n<h3>5.2 Seats Not Available for First-Time Selectees Due to “Selected at Least Once” Candidates<\/h3>\n<p>Our cleaned data shows that 20.8% of 2024 selections and 37.6% of IAS seats went to SAO candidates. The adjacent-year data (Chapter 3) shows ~8.5\u201311.3% of selectees immediately re-appear, with ~66\u201376% from Central Services and ~19\u201332% from IPS. Each repeated selection creates a cascading displacement chain through the service ladder.<\/p>\n\n<h3>5.3 Projected Impact<\/h3>\n<p>If the 2026 rules had been in effect, approximately <strong>~125 additional seats per year<\/strong> (averaging across the four analysis years) would have been freed for first-time selectees. For IAS, approximately <strong>~44 additional first-time selectee seats<\/strong> per year \u2014 a meaningful improvement in selection probability.<\/p>\n\n<h3>5.4 The Debate<\/h3>\n<p>Proponents argue for a more level playing field for first-time selectees. Critics counter that restrictions may limit legitimate career choices. UPSC’s stated rationale: administrative efficiency, training resource optimisation, and fairness to new entrants.<\/p>\n\n<div class=\"separator\">\u2022 \u2022 \u2022<\/div>\n\n\n<h2 id=\"ch6\"><span class=\"chapter-label\">Chapter Six<\/span>The Economics of Repetition \u2014 Opportunity Costs, Near-Term Salary Loss, and Superannuation Penalties<\/h2>\n\n<p>Engaging in repeated examination cycles carries a profound financial penalty \u2014 the <strong>opportunity cost<\/strong>. This manifests in two devastating phases: the immediate hemorrhage of near-future earnings, and the compounding destruction of terminal wealth and pension benefits at superannuation.<\/p>\n\n<h3>6.1 The Financial Architecture of the Civil Services (7th Pay Commission)<\/h3>\n<p>Promotions are bound to <strong>years of service<\/strong>, not age or rank. This makes the year of entry the single most consequential financial variable in an officer’s career.<\/p>\n\n<div class=\"ladder\">\n<div class=\"ladder-step\"><span class=\"level\">Level 18<\/span><span class=\"desc\">Cabinet Secretary (37+ yrs)<\/span><span class=\"pay\">\u20b92,50,000<\/span><\/div>\n<div class=\"ladder-step\"><span class=\"level\">Level 17<\/span><span class=\"desc\">Apex Scale (34\u201336 yrs)<\/span><span class=\"pay\">\u20b92,25,000<\/span><\/div>\n<div class=\"ladder-step\"><span class=\"level\">Level 15<\/span><span class=\"desc\">Above Super Time Scale (25\u201330 yrs)<\/span><span class=\"pay\">\u20b91,82,200<\/span><\/div>\n<div class=\"ladder-step\"><span class=\"level\">Level 14<\/span><span class=\"desc\">Super Time Scale (16\u201324 yrs)<\/span><span class=\"pay\">\u20b91,44,200<\/span><\/div>\n<div class=\"ladder-step\"><span class=\"level\">Level 12<\/span><span class=\"desc\">Jr. Administrative Grade (9\u201312 yrs)<\/span><span class=\"pay\">\u20b978,800<\/span><\/div>\n<div class=\"ladder-step\"><span class=\"level\">Level 11<\/span><span class=\"desc\">Senior Time Scale (4\u20139 yrs)<\/span><span class=\"pay\">\u20b967,700<\/span><\/div>\n<div class=\"ladder-step\" style=\"border-left-color:var(--sage)\"><span class=\"level\">Level 10<\/span><span class=\"desc\">Junior Scale \u2014 Entry Level (0\u20134 yrs)<\/span><span class=\"pay\">\u20b956,100<\/span><\/div>\n<\/div>\n<p style=\"font-size:.85em;color:var(--warm-gray);font-style:italic;text-align:center\">Gross monthly at entry scales to \u20b990,000\u2013\u20b91,00,000 with DA, HRA, and TA.<\/p>\n\n<h3>6.2 The Near-Term Salary Haemorrhage<\/h3>\n<table>\n<thead><tr><th>Delay Period<\/th><th>Salary Foregone (Govt.)<\/th><th>Salary Foregone (Private, Premier Grad.)<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>1 year<\/td><td class=\"num\">\u20b910\u201312 lakh<\/td><td class=\"num\">\u20b98\u201315 lakh<\/td><\/tr>\n<tr><td>2 years<\/td><td class=\"num\">\u20b920\u201324 lakh<\/td><td class=\"num\">\u20b918\u201332 lakh<\/td><\/tr>\n<tr><td>3 years<\/td><td class=\"num\">\u20b930\u201336 lakh<\/td><td class=\"num\">\u20b928\u201350 lakh<\/td><\/tr>\n<tr><td>5 years<\/td><td class=\"num\">\u20b955\u201365 lakh<\/td><td class=\"num\">\u20b960\u20131.0 crore<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<h3>6.3 The Mathematics of Compounding: Wealth Destruction Through Delay<\/h3>\n<p><strong>Candidate A<\/strong> \u2014 Enters workforce at 23. Invests \u20b940,000\/month (10% return) for 5 years (age 23\u201328), then stops adding money.<\/p>\n<p><strong>Candidate B<\/strong> \u2014 Prepares full-time ages 23\u201328. Zero income. Enters service at 28.<\/p>\n\n<table>\n<thead><tr><th>Financial Metric<\/th><th>Candidate A (Enters at 23)<\/th><th>Candidate B (Enters at 28)<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>Action, age 23\u201328<\/td><td>Works, invests \u20b940,000\/month<\/td><td>Studies. \u20b90 income, \u20b90 invested<\/td><\/tr>\n<tr><td>Capital by age 28<\/td><td class=\"num\">\u20b924 lakh (principal)<\/td><td class=\"num\">\u20b90<\/td><\/tr>\n<tr><td>Action, age 28\u201360<\/td><td>Stops adding. Lets corpus compound 32 years<\/td><td>Starts working. Must catch up<\/td><\/tr>\n<tr><td><strong>Corpus at 60 from early investment alone<\/strong><\/td><td class=\"pct\"><strong>~\u20b95.25 crore<\/strong><\/td><td class=\"num\"><strong>\u20b90 from this window<\/strong><\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<p>Candidate A’s \u20b924 lakh grows to over <strong>\u20b95 crore<\/strong> purely from time-in-market. The five years of lost compounding destroys roughly <strong>\u20b92 crore<\/strong> from this tranche alone.<\/p>\n\n<h3>6.4 Full Career Compounding Impact<\/h3>\n\n<div class=\"chart-container\">\n<div class=\"chart-title\">Compounding Curves: Candidate A (37 yrs) vs Candidate B (32 yrs)<\/div>\n<canvas id=\"compoundChart\" height=\"280\"><\/canvas>\n<div class=\"chart-note\">10% CAGR, \u20b95L starting annual savings, 5% annual increment. A ends at ~\u20b931Cr, B at ~\u20b918Cr. Delta: ~\u20b913 crore at age 60.<\/div>\n<\/div>\n\n<table>\n<thead><tr><th>Parameter<\/th><th>Candidate A (37 years)<\/th><th>Candidate B (32 years)<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>Total investment years<\/td><td class=\"num\">37<\/td><td class=\"num\">32<\/td><\/tr>\n<tr><td>Starting annual savings<\/td><td class=\"num\">\u20b95,00,000<\/td><td class=\"num\">\u20b95,00,000<\/td><\/tr>\n<tr><td>Annual increment<\/td><td class=\"num\">5%<\/td><td class=\"num\">5%<\/td><\/tr>\n<tr><td>Return rate<\/td><td class=\"num\">10% CAGR<\/td><td class=\"num\">10% CAGR<\/td><\/tr>\n<tr><td><strong>Corpus at age 60<\/strong><\/td><td class=\"pct\"><strong>~\u20b931.0 crore<\/strong><\/td><td class=\"num\">~\u20b918.2 crore<\/td><\/tr>\n<tr><td><strong>Difference<\/strong><\/td><td colspan=\"2\" style=\"text-align:center\" class=\"pct\"><strong>~\u20b912.8 crore less<\/strong><\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<h3>6.5 The Superannuation Penalty \u2014 The Career Ceiling Effect<\/h3>\n<table>\n<thead><tr><th>Entry Age<\/th><th>Years of Service (Retire at 60)<\/th><th>Terminal Pay Level<\/th><th>Terminal Basic Pay<\/th><\/tr><\/thead>\n<tbody>\n<tr><td class=\"num\">23<\/td><td class=\"num\">37 years<\/td><td>Level 17\u201318 (Apex \/ Cabinet Secy.)<\/td><td class=\"num\">\u20b92,25,000\u2013\u20b92,50,000<\/td><\/tr>\n<tr><td class=\"num\">25<\/td><td class=\"num\">35 years<\/td><td>Level 17 (Apex Scale)<\/td><td class=\"num\">\u20b92,25,000<\/td><\/tr>\n<tr><td class=\"num\">28<\/td><td class=\"num\">32 years<\/td><td>Level 15\u201316<\/td><td class=\"num\">\u20b91,82,200\u2013\u20b92,05,400<\/td><\/tr>\n<tr><td class=\"num\">30<\/td><td class=\"num\">30 years<\/td><td>Level 14\u201315<\/td><td class=\"num\">\u20b91,44,200\u2013\u20b91,82,200<\/td><\/tr>\n<tr><td class=\"num\">32<\/td><td class=\"num\">28 years<\/td><td>Level 14<\/td><td class=\"num\">\u20b91,44,200<\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<p>Because <strong>pensions are derived from the last drawn salary<\/strong>, years spent preparing for exams directly amputate the highest-paying years \u2014 a <strong>lifelong financial penalty<\/strong> extending into retirement. The pension differential between Level 15 and Level 17 is approximately <strong>\u20b940,000\u2013\u20b965,000 per month<\/strong>, or <strong>\u20b95\u20138 lakh per year<\/strong>. Over a 20\u201325 year retirement, this exceeds <strong>\u20b91\u20132 crore<\/strong>.<\/p>\n\n<h3>6.6 The Private Sector Comparison<\/h3>\n<p>A premier-institution graduate taking a private sector job at 23, investing \u20b94 lakh\/year at 10% for 37 years with 8% annual increment, accumulates approximately <strong>\u20b912\u201315 crore<\/strong> \u2014 comparable to or exceeding civil services, with more career flexibility and no examination stress. The point is not that private employment is superior \u2014 civil services offer irreplaceable public impact and constitutional authority \u2014 but the financial cost of delay is <strong>substantial, mathematically irreversible, and almost universally underestimated<\/strong>.<\/p>\n\n<h3>6.7 Total Cost of a 5-Year Delay<\/h3>\n\n<div class=\"stat-grid\">\n<div class=\"stat-card\"><span class=\"big\">\u20b955\u201365L<\/span><span class=\"label\">Direct salary foregone<\/span><\/div>\n<div class=\"stat-card\"><span class=\"big\">\u20b92\u201313Cr<\/span><span class=\"label\">Lost compounding<\/span><\/div>\n<div class=\"stat-card\"><span class=\"big\">1\u20132 levels<\/span><span class=\"label\">Reduced terminal pay<\/span><\/div>\n<div class=\"stat-card\"><span class=\"big\">\u20b91\u20132Cr<\/span><span class=\"label\">Pension loss (20 yrs)<\/span><\/div>\n<\/div>\n\n<table>\n<thead><tr><th>Cost Component<\/th><th>Approximate Value<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>Direct salary foregone (5 years)<\/td><td class=\"num\">\u20b955\u201365 lakh<\/td><\/tr>\n<tr><td>Lost compounding on early-career savings<\/td><td class=\"num\">\u20b92\u201313 crore<\/td><\/tr>\n<tr><td>Reduced terminal pay level<\/td><td>1\u20132 pay levels lower<\/td><\/tr>\n<tr><td>Cumulative pension loss over 20-year retirement<\/td><td class=\"num\">\u20b91\u20132 crore<\/td><\/tr>\n<tr><td><strong>Total lifetime financial impact<\/strong><\/td><td class=\"pct\"><strong>\u20b94\u201317 crore<\/strong><\/td><\/tr>\n<\/tbody>\n<\/table>\n\n<p>The years between 22 and 28 are the <strong>most financially consequential years<\/strong> of an officer’s career \u2014 they sit at the base of the compounding curve.<\/p>\n\n<div class=\"separator\">\u2022 \u2022 \u2022<\/div>\n\n\n<h2 id=\"ch7\"><span class=\"chapter-label\">Chapter Seven<\/span>Why Candidates Should Give Their Best Shot at the First Attempt \u2014 or the Repeated First Attempt<\/h2>\n\n<h3>7.1 The Data Makes the Case<\/h3>\n<p>The analysis converges on a single insight: <strong>the examination rewards decisive, well-prepared attempts over prolonged, incremental re-tries.<\/strong><\/p>\n\n<h3>7.2 The Odds Do Not Improve with Repetition<\/h3>\n<p><strong>Syllabus evolution<\/strong>: Current affairs are entirely new each cycle. Additional years add the burden of staying current alongside deepening existing knowledge.<\/p>\n<p><strong>Diminishing returns<\/strong>: The first 6\u201312 months yield the steepest improvement. Subsequent years show diminishing marginal gains.<\/p>\n<p><strong>Psychological erosion<\/strong>: Self-doubt, comparison anxiety, and burnout can reduce performance in subsequent attempts, creating a vicious cycle.<\/p>\n\n<h3>7.3 The “Repeated First Attempt” Philosophy<\/h3>\n<p>The most successful candidates treat <strong>every attempt as if it’s their only one<\/strong> \u2014 100% preparation intensity each cycle. The data supports this: <strong>88.3%<\/strong> of unique individuals in our analysis years appear only once in the allocation lists.<\/p>\n\n<h3>7.4 The Changing Regulatory Landscape<\/h3>\n<p>CSE 2026 introduces strict re-attempt restrictions. The “join a lower service, upgrade later” strategy now carries: mandatory resignation from CSE 2028 onward, loss of seniority, a single one-time improvement window, and the psychological burden of having something to lose.<\/p>\n\n<h3>7.5 The Adjacent-Year Evidence (Chapter 3 Revisited)<\/h3>\n<p>Even among the most determined re-selectors \u2014 those returning in the very next year \u2014 only ~58\u201368% achieve a service upgrade. ~33\u201342% are allocated IAS in the subsequent selection. The remaining ~32\u201342% stay in the same tier or move to a different one.<\/p>\n\n<h3>7.6 A Framework for Decision-Making<\/h3>\n<p>Before re-attempting, evaluate honestly:<\/p>\n<p><strong>Marginal benefit<\/strong>: Is the target service significantly different in career satisfaction and lifestyle? IPS, IFS, and Central Services offer deeply fulfilling careers.<\/p>\n<p><strong>Marginal cost<\/strong>: A 3-year delay costs several crores in terminal wealth. A 5-year delay can destroy \u20b94\u201317 crore in lifetime financial value \u2014 including lost compounding, reduced terminal pay, and diminished pension.<\/p>\n<p><strong>Marginal probability<\/strong>: Of 456 SAO candidates, only 163 (35.7%) ultimately landed in IAS \u2014 nearly two-thirds did not achieve the IAS allocation despite multiple selections.<\/p>\n<p><strong>Changing rules<\/strong>: CSE 2026 norms introduce resignation risk, training disruption, and irreversible administrative consequences.<\/p>\n\n<h3>7.7 The Bottom Line<\/h3>\n<div class=\"callout\">\nEvery attempt is precious. Every year of career is irreplaceable. The numbers are clear: <strong>prepare well, execute decisively, and make your attempt count.<\/strong>\n<\/div>\n\n<div class=\"separator\">\u2767<\/div>\n\n\n<div class=\"footer-note\">\n<p><strong>Analysis<\/strong>: Purushottam B. | <strong>Data<\/strong>: UPSC Service Allocation Lists 2020\u20132024 | <strong>AI Assistance<\/strong>: Claude (Anthropic)<\/p>\n<p><strong>Methodology<\/strong>: Official UPSC service allocation files for CSE 2020\u20132024 parsed using Python (pandas). Names standardised to uppercase with special characters removed. <strong>Data cleaning<\/strong>: 10 true duplicate rows removed; 33 ambiguous common names excluded from all cross-year matching. CSE 2020 (673 usable candidates) used as reference year. Analysis covers CSE 2021\u20132024 (3,303 usable allocations, 2,939 unique individuals). Adjacent-year and service trajectory analyses based on actual name-matching of usable names only. Aggregate examination statistics from PIB press releases.<\/p>\n<p>Published on <a href=\"https:\/\/basavapurushottam.com\">Stories Through Data<\/a> (basavapurushottam.com)<\/p>\n<\/div>\n\n<\/article>\n\n\n\n\n<script>\nconst amber='#c17817',rust='#a0522d',deepRust='#8b3a1a',sage='#5a6b52',warmGray='#6b5e50',cream='#faf6ee',ink='#1a1714',parchment='#f5f0e8';\nChart.defaults.font.family=\"'Cormorant Garamond',Georgia,serif\";\nChart.defaults.font.size=13;\nChart.defaults.color=ink;\n\n\/\/ Ch2: SAO Trend\nnew Chart(document.getElementById('saoTrendChart'),{\n type:'bar',\n data:{\n labels:['2021','2022','2023','2024'],\n datasets:[\n {label:'First-Time Selectees',data:[586,666,808,743],backgroundColor:sage,order:2},\n {label:'Selected at Least Once',data:[57,101,147,195],backgroundColor:amber,order:2},\n {label:'SAO %',data:[8.9,13.2,15.4,20.8],type:'line',borderColor:deepRust,backgroundColor:'transparent',pointBackgroundColor:deepRust,pointRadius:5,borderWidth:2.5,yAxisID:'pct',order:1}\n ]\n },\n options:{\n responsive:true,\n scales:{\n x:{stacked:true,grid:{display:false}},\n y:{stacked:true,title:{display:true,text:'Candidates'},grid:{color:'#e0d8cc'}},\n pct:{position:'right',min:0,max:30,title:{display:true,text:'SAO %'},ticks:{callback:v=>v+'%'},grid:{display:false}}\n },\n plugins:{legend:{position:'bottom',labels:{padding:16}}}\n }\n});\n\n\/\/ Ch2: Frequency Donut\nnew Chart(document.getElementById('freqChart'),{\n type:'doughnut',\n data:{\n labels:['1 time (88.3%)','2 times (11.1%)','3 times (0.5%)','4 times (0.1%)'],\n datasets:[{data:[2595,326,16,2],backgroundColor:[sage,amber,rust,deepRust],borderWidth:2,borderColor:cream}]\n },\n options:{responsive:true,plugins:{legend:{position:'bottom',labels:{padding:12}}}}\n});\n\n\/\/ Ch2: Overlap heatmap as grouped bar\nnew Chart(document.getElementById('overlapChart'),{\n type:'bar',\n data:{\n labels:['2020\u219221','2020\u219222','2020\u219223','2020\u219224','2021\u219222','2021\u219223','2021\u219224','2022\u219223','2022\u219224','2023\u219224'],\n datasets:[{label:'Shared Candidates',data:[57,49,29,25,56,47,21,87,73,102],backgroundColor:function(ctx){return ctx.dataIndex>=7?amber:ctx.dataIndex>=4?rust:warmGray}}]\n },\n options:{\n responsive:true,indexAxis:'y',\n scales:{x:{grid:{color:'#e0d8cc'},title:{display:true,text:'Candidates in Common'}},y:{grid:{display:false}}},\n plugins:{legend:{display:false}}\n }\n});\n\n\/\/ Ch3: Feeder service stacked\nnew Chart(document.getElementById('feederChart'),{\n type:'bar',\n data:{\n labels:['2020\u219221','2021\u219222','2022\u219223','2023\u219224'],\n datasets:[\n {label:'From Central Services',data:[40,37,63,77],backgroundColor:warmGray},\n {label:'From IPS',data:[13,18,17,21],backgroundColor:sage},\n {label:'From IAS',data:[3,1,7,3],backgroundColor:amber},\n {label:'From IFS',data:[1,0,0,1],backgroundColor:rust}\n ]\n },\n options:{\n responsive:true,scales:{x:{stacked:true,grid:{display:false}},y:{stacked:true,grid:{color:'#e0d8cc'},title:{display:true,text:'Candidates'}}},\n plugins:{legend:{position:'bottom',labels:{padding:12}}}\n }\n});\n\n\/\/ Ch3: Upgrade outcome\nnew Chart(document.getElementById('upgradeChart'),{\n type:'bar',\n data:{\n labels:['2020\u219221','2021\u219222','2022\u219223','2023\u219224'],\n datasets:[\n {label:'Upgraded',data:[39,33,50,64],backgroundColor:sage},\n {label:'Same Tier',data:[12,17,27,31],backgroundColor:amber},\n {label:'Different Tier',data:[6,6,10,7],backgroundColor:rust}\n ]\n },\n options:{\n responsive:true,scales:{x:{stacked:true,grid:{display:false}},y:{stacked:true,grid:{color:'#e0d8cc'},title:{display:true,text:'Candidates'}}},\n plugins:{legend:{position:'bottom',labels:{padding:12}}}\n }\n});\n\n\/\/ Ch3: Transitions horizontal bar\nnew Chart(document.getElementById('transChart'),{\n type:'bar',\n data:{\n labels:['OCS\u2192OCS','OCS\u2192IAS','OCS\u2192IPS','IPS\u2192IAS','IPS\u2192OCS','OCS\u2192IFS','IPS\u2192IFS','IPS\u2192IPS','IAS\u2192OCS','IAS\u2192IAS','IAS\u2192IPS','IFS\u2192IAS','IFS\u2192IPS'],\n datasets:[{\n data:[76,68,61,36,19,12,8,6,6,5,3,1,1],\n backgroundColor:function(ctx){\n const ups=[1,2,3,5,6];const same=[0,7,9];\n if(ups.includes(ctx.dataIndex))return sage;\n if(same.includes(ctx.dataIndex))return amber;\n return rust;\n }\n }]\n },\n options:{\n responsive:true,indexAxis:'y',\n scales:{x:{grid:{color:'#e0d8cc'},title:{display:true,text:'Count'}},y:{grid:{display:false},ticks:{font:{size:11}}}},\n plugins:{legend:{display:false}}\n }\n});\n\n\/\/ Ch4: SAO % by service over time\nnew Chart(document.getElementById('svcSaoChart'),{\n type:'line',\n data:{\n labels:['2021','2022','2023','2024'],\n datasets:[\n {label:'IAS',data:[13.7,22.3,26.4,37.6],borderColor:deepRust,backgroundColor:'transparent',pointBackgroundColor:deepRust,pointRadius:5,borderWidth:2.5,tension:.3},\n {label:'IFS',data:[8.3,13.8,22.2,28.8],borderColor:amber,backgroundColor:'transparent',pointBackgroundColor:amber,pointRadius:5,borderWidth:2,tension:.3},\n {label:'IPS',data:[9.1,12.9,17.4,28.3],borderColor:sage,backgroundColor:'transparent',pointBackgroundColor:sage,pointRadius:5,borderWidth:2,tension:.3},\n {label:'Other Central Services',data:[5.1,9.7,10.8,13.1],borderColor:warmGray,backgroundColor:'transparent',pointBackgroundColor:warmGray,pointRadius:4,borderWidth:1.5,borderDash:[5,3],tension:.3}\n ]\n },\n options:{\n responsive:true,\n scales:{y:{min:0,max:45,ticks:{callback:v=>v+'%'},grid:{color:'#e0d8cc'},title:{display:true,text:'% SAO'}},x:{grid:{display:false}}},\n plugins:{legend:{position:'bottom',labels:{padding:14}}}\n }\n});\n\n\/\/ Ch4: Trajectory donut\nnew Chart(document.getElementById('trajChart'),{\n type:'doughnut',\n data:{\n labels:['Upgraded (59.6%)','Same Tier (28.7%)','Different Tier (11.6%)'],\n datasets:[{data:[272,131,53],backgroundColor:[sage,amber,rust],borderWidth:2,borderColor:cream}]\n },\n options:{responsive:true,plugins:{legend:{position:'bottom',labels:{padding:14}}}}\n});\n\n\/\/ Ch6: Compounding curves \u2014 Section 6.4: Full career continuous saving\n\/\/ A saves continuously age 23\u201360 (37 years), B saves continuously age 28\u201360 (32 years)\n\/\/ Both: \u20b95L\/year starting, 5% annual increment, 10% CAGR\n(function(){\n const labels=[],a=[],b=[];\n let corpusA=0,corpusB=0,savA=500000,savB=500000;\n for(let age=23;age<=60;age++){\n labels.push(age);\n \/\/ A saves every year from 23 onward\n corpusA = corpusA * 1.10 + savA;\n savA *= 1.05;\n \/\/ B only starts saving from age 28\n if(age >= 28){\n corpusB = corpusB * 1.10 + savB;\n savB *= 1.05;\n }\n a.push(Math.round(corpusA\/1000000)\/10);\n b.push(Math.round(corpusB\/1000000)\/10);\n }\n new Chart(document.getElementById('compoundChart'),{\n type:'line',\n data:{\n labels:labels,\n datasets:[\n {label:'Candidate A (enters at 23)',data:a,borderColor:sage,backgroundColor:'rgba(90,107,82,0.1)',fill:true,pointRadius:0,borderWidth:2.5,tension:.3},\n {label:'Candidate B (enters at 28)',data:b,borderColor:rust,backgroundColor:'rgba(160,82,45,0.1)',fill:true,pointRadius:0,borderWidth:2.5,tension:.3}\n ]\n },\n options:{\n responsive:true,\n scales:{\n x:{title:{display:true,text:'Age'},grid:{display:false},ticks:{callback:function(v,i){return i%5===0?labels[i]:''}}},\n y:{title:{display:true,text:'Corpus (\u20b9 Crore)'},grid:{color:'#e0d8cc'},ticks:{callback:v=>'\u20b9'+v+'Cr'}}\n },\n plugins:{legend:{position:'bottom',labels:{padding:14}}}\n }\n });\n})();\n<\/script>\n\n<\/body>\n<\/html>\n","protected":false},"excerpt":{"rendered":"<p>UPSC CSE: A Probabilistic Analysis of Selection Patterns (2021\u20132024) UPSC Civil Services Examination: A Probabilistic Analysis of Selection Patterns (2021\u20132024) First-Timers vs. Candidates “Selected at Least Once” \u2014 What the Data Reveals \u26a0 Disclaimer This analysis is generated with AI assistance. The data has been parsed from official UPSC service allocation lists (2020\u20132024) using automated […]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"off","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[1],"tags":[176],"class_list":["post-3087","post","type-post","status-publish","format-standard","hentry","category-blog","tag-upsc"],"_links":{"self":[{"href":"https:\/\/basavapurushottam.com\/index.php\/wp-json\/wp\/v2\/posts\/3087","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/basavapurushottam.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/basavapurushottam.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/basavapurushottam.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/basavapurushottam.com\/index.php\/wp-json\/wp\/v2\/comments?post=3087"}],"version-history":[{"count":2,"href":"https:\/\/basavapurushottam.com\/index.php\/wp-json\/wp\/v2\/posts\/3087\/revisions"}],"predecessor-version":[{"id":3089,"href":"https:\/\/basavapurushottam.com\/index.php\/wp-json\/wp\/v2\/posts\/3087\/revisions\/3089"}],"wp:attachment":[{"href":"https:\/\/basavapurushottam.com\/index.php\/wp-json\/wp\/v2\/media?parent=3087"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/basavapurushottam.com\/index.php\/wp-json\/wp\/v2\/categories?post=3087"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/basavapurushottam.com\/index.php\/wp-json\/wp\/v2\/tags?post=3087"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}