---
conjecture: r3-b1-26
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": "A portal-wide form or ingestion-template constraint makes language and script fields co-missing: when language is blank or malformed, script is usually also absent or unusable. The pathway is therefore rare across every state regardless of any Tibetan-specific institutional practice.",
      "why_it_explains_the_same_evidence": "Because all states use the same portal and likely share forms, import schemas, or validation rules, coupled field completion would keep the script-only pathway below 2% in both training and holdout states. The 1.60% maximum could reflect one import batch or source template that permitted script without valid language, rather than a state-specific Tibetan cataloguing norm.",
      "named_confounds": [
        "portal-wide data-entry field coupling",
        "shared ingestion-template artifact",
        "batch-specific metadata completeness"
      ],
      "discriminating_test": {
        "description": "For every record with unusable language, measure usable-script frequency by source institution, ingestion batch, template, and state. A template-level model should then be compared with a state-by-Tibetan-presence model, including comparisons of the same template across states.",
        "computable_on_held_data": true,
        "what_result_favors_rival": "Usable-script frequencies cluster by shared template or ingestion batch across multiple states, with little residual Tibetan-state effect after controlling for those batches."
      }
    },
    {
      "mechanism": "The statewide percentages are kept low by denominator composition: large, standardized institutional inventories with usable language metadata dominate each state's record count, diluting small collections or batches where script-only routing is common. This is a holdings-mixture effect rather than a distinctive state cataloguing mechanism.",
      "why_it_explains_the_same_evidence": "NAMAMI states are holding locations, so each state-level rate is a weighted mixture of heterogeneous contributing institutions rather than a coherent production tradition. If standardized high-volume institutions dominate both training and holdout denominators, every aggregate can remain below 2% even when some constituent collections have much higher rates; the training maximum can arise from that state's particular mixture weights.",
      "named_confounds": [
        "state-level denominator dilution",
        "institutional holdings-mixture confounding",
        "selective cataloguing of standardized inventories"
      ],
      "discriminating_test": {
        "description": "Compute the pathway share separately for each holding institution or collection, then recompute state rates using equal institution weights and a common set of institution-size weights. Test whether the observed state ranking and universal sub-2% result persist after this standardization.",
        "computable_on_held_data": true,
        "what_result_favors_rival": "Multiple small institutions or collections, especially non-Tibetan ones, exceed 2%, and equal-weighted or standardized state rates differ sharply from the published record-weighted rates or eliminate the Tibetan-presence state's maximum."
      }
    },
    {
      "mechanism": "The low rate is largely induced by the operational mapping from script tokens to traditions: only unusually diagnostic scripts, such as Tibetan, can qualify as sufficient by themselves, while common scripts shared by many traditions are excluded. Script-to-tradition identifiability, not a state's cataloguing behavior, therefore creates both the Tibetan-associated maximum and the low ceiling elsewhere.",
      "why_it_explains_the_same_evidence": "The same script-to-tradition mapping is applied throughout the portal, so states dominated by non-diagnostic scripts will necessarily have very small qualifying numerators in both training and holdout data. A state with more Tibetan-script holdings will mechanically approach the maximum because Tibetan script is more informative under that mapping, even if its cataloguers behave no differently from those elsewhere.",
      "named_confounds": [
        "script-to-tradition ontology artifact",
        "outcome-definition dependence",
        "state differences in script composition"
      ],
      "discriminating_test": {
        "description": "Recalculate shares under several pre-specified tradition taxonomies and independently audited script-to-tradition mappings, and standardize every state to a common script-frequency distribution. Measure whether the state maximum and distance from 2% are stable across mappings and after script-mix standardization.",
        "computable_on_held_data": true,
        "what_result_favors_rival": "Rates and state rankings change substantially with taxonomy or mapping choice, and the Tibetan-presence state's excess disappears after standardizing script composition, leaving no residual state-specific effect."
      }
    }
  ],
  "no_viable_rival": false,
  "notes": ""
}
