---
conjecture: r3-b1-17
family: codex
model: "gpt-5.6-sol (codex-cli 0.144.0-alpha.4, ChatGPT-subscription auth)"
model_stamp_corrected: "2026-08-07 — archives were first written stamped gpt-5.5 by a runner bug (the stamper read config.toml's default instead of the -m flag actually passed). The calls themselves ran on gpt-5.6-sol throughout; only the label was wrong. Corrected in place, noted here rather than silently."
received: 2026-08-07
template: PROMPT_TEMPLATE_v1.md sha256 4344aabfacfe88362c56d89b6c89d594a7bf3a221e18a16b0e351482447e512f
rivals_parsed: 3
validation: VALID
---

{
  "rivals": [
    {
      "mechanism": "The rank-size shape may be produced by preferential cataloguing effort: survey teams catalogue major repositories deeply while recording many smaller institutions only shallowly. A complete portal walk would then measure a stable allocation of cataloguing effort rather than the distribution of actual holdings accumulated by institutions.",
      "why_it_explains_the_same_evidence": "A common nationwide survey protocol could impose a similar depth-by-institution-rank profile in every state, yielding approximately linear log-rank plots and high R-squared values even when total state-level effort varies greatly. Because the holdout states used the same portal and cataloguing system, they would reproduce this profile, including occasional territories represented by only one surveyed institution.",
      "named_confounds": [
        "preferential cataloguing of major repositories",
        "institution-specific variation in catalogue completeness",
        "selection effects in which holdings were catalogued"
      ],
      "discriminating_test": {
        "description": "Obtain independent inventory totals for a stratified sample of large, medium, and small institutions, calculate each institution's portal capture fraction, and recompute state distributions after correcting observed counts for capture fraction.",
        "computable_on_held_data": false,
        "what_result_favors_rival": "The rival is favored if capture fractions vary systematically with observed rank or institution size and coverage-adjusted distributions cease to be approximately log-linear, leave the registered slope band, or show substantially reduced R-squared."
      }
    },
    {
      "mechanism": "The apparent heavy tail may arise from institution-dependent record unitization: imported legacy catalogues at major repositories may create multiple portal records per physical manuscript, while smaller collections may receive one coarse record per manuscript or bundle. Observed counts would therefore combine holdings with a size-correlated record-expansion factor.",
      "why_it_explains_the_same_evidence": "Large repositories are especially likely to possess detailed catalogues that split composite manuscripts, works, copies, or duplicate imports into separate records. Applying this practice through one portal can repeatedly amplify the head of each state's distribution, producing steep, high-fit rank plots in both training and holdout states without requiring a common holdings-accumulation process.",
      "named_confounds": [
        "record-versus-physical-manuscript unit-of-count effect",
        "institution-dependent cataloguing granularity",
        "duplicate or multi-work record expansion"
      ],
      "discriminating_test": {
        "description": "Using record-level pages from the same catalogue, collapse records within institution by stable shelfmark or physical-object identifier and separately deduplicate near-identical records; then refit every state's rank-count slope and compare institution-specific compression ratios.",
        "computable_on_held_data": true,
        "what_result_favors_rival": "The rival is favored if high-ranked institutions have much larger record-to-object ratios and object-normalization materially flattens or curves the distributions, moves slopes outside the registered band, or sharply lowers their R-squared."
      }
    },
    {
      "mechanism": "A recurring mixture of administrative institution classes could generate the pooled rank curve: each state contains a few designated public repositories, several university or specialist libraries, and many small religious or private collections with class-specific capacities. The shape would then reflect institutional stratification rather than a scale-free accumulation dynamic.",
      "why_it_explains_the_same_evidence": "Indian states can share broadly similar repository hierarchies even while differing greatly in total holdings. Pooling several capacity tiers can approximate a straight line over a finite log-rank range, so the same institutional composition could account for both the training slopes and replication across additional states.",
      "named_confounds": [
        "compositional mixture of institution types",
        "administrative repository hierarchy",
        "between-class capacity differences"
      ],
      "discriminating_test": {
        "description": "Classify institutions from catalogue names and metadata into preregistered administrative types, estimate class effects within states, and recompute rank-count relationships within each type and on residual counts after removing state-by-type means.",
        "computable_on_held_data": true,
        "what_result_favors_rival": "The rival is favored if most count variation is between institution classes while within-class or class-adjusted distributions are near-uniform, strongly curved, or consistently fail the registered slope criterion."
      }
    }
  ],
  "no_viable_rival": false,
  "notes": "Replication across states within one portal is strong evidence for internal regularity, but it does not independently test mechanisms shared by the portal's survey, record-construction, or institution-classification practices."
}
