---
conjecture: r2-edh-b1-01
family: codex
model: "gpt-5.5 (codex-cli 0.144.0-alpha.4, ChatGPT-subscription auth)"
received: 2026-08-07
template: PROMPT_TEMPLATE_v1.md sha256 4344aabfacfe88362c56d89b6c89d594a7bf3a221e18a16b0e351482447e512f
rivals_parsed: 3
validation: VALID
---

{
  "rivals": [
    {
      "mechanism": "The concentration may reflect the ancient distribution of inscribing activity rather than modern recovery effort: provinces with larger urban populations, denser military or administrative presence, stronger epigraphic habits, or better pre-modern survival would genuinely have produced and retained more inscriptions. An arbitrary alphabetical split would still leave a few high-supply provinces in each half.",
      "why_it_explains_the_same_evidence": "If inscription supply was highly uneven before modern excavation began, then both the training half and the holdout half would naturally have long-tailed provincial counts. The observed 64.21% training concentration and 48.77% holdout concentration would follow from real ancient and taphonomic heterogeneity, without requiring the top provinces to be the ones most intensively excavated or collected in modern times.",
      "named_confounds": [
        "ancient epigraphic habit",
        "ancient population and urbanization density",
        "military and administrative presence",
        "pre-modern survival and taphonomic preservation"
      ],
      "discriminating_test": {
        "description": "Model provincial inscription counts using independent ancient-supply and preservation predictors, such as ancient urban-site counts, estimated population, legionary or military-site density, road density, stone availability, and preservation or reuse proxies, and compare this with a model using modern excavation/publication/recovery proxies. Measure which model better predicts holdout provincial ranks and whether the top-five share remains high after controlling for the relevant predictors.",
        "computable_on_held_data": false,
        "what_result_favors_rival": "The rival is favored if ancient-supply and preservation variables predict the high-count holdout provinces and remove most residual top-five concentration, while modern excavation/recovery proxies add little explanatory power."
      }
    },
    {
      "mechanism": "The result may be an administrative-unit denominator artifact: EDH province labels may group territories that differ greatly in area, number of settlements, and internal heterogeneity. Larger or coarser province units would accumulate more inscriptions simply because they contain more places, not because recovery effort is especially concentrated there.",
      "why_it_explains_the_same_evidence": "A top-five share above 45% is expected if the province units themselves are uneven containers. Both the training and holdout halves contain a mixture of large/coarse and small/fine province categories, so the largest containers in each half would dominate totals under the alphabetical split.",
      "named_confounds": [
        "administrative classification artifact",
        "province-size denominator effect",
        "unequal geographic granularity",
        "findspot-count denominator effect"
      ],
      "discriminating_test": {
        "description": "Using the same catalogue re-queried at findspot or coordinate level, normalize each province by number of distinct findspots, settled places, or equal-area grid cells, then recompute concentration using standardized spatial units rather than EDH province labels. Compare the top-five share before and after standardization.",
        "computable_on_held_data": true,
        "what_result_favors_rival": "The rival is favored if the top-five concentration collapses after controlling for province size, number of findspots, or equal-area units, and if the original top provinces are high mainly because they contain more places rather than more inscriptions per place."
      }
    },
    {
      "mechanism": "The pattern may be driven by EDH source-ingestion or bibliographic coverage rather than by recovery itself: some provinces may be overrepresented because major corpora, regional publications, or digitization batches covering them were more completely harvested into EDH. This would create provincial concentration in the database even if the underlying recovered material was less concentrated.",
      "why_it_explains_the_same_evidence": "If EDH coverage is uneven by source publication or import batch, each alphabetical half can contain a few provinces whose relevant corpora were especially completely digitized. That would produce high top-five shares in both training and holdout, including a passed holdout result, without requiring a province-level excavation-effort mechanism.",
      "named_confounds": [
        "catalogue coverage bias",
        "bibliographic harvest artifact",
        "digitization batch effect",
        "source-publication completeness"
      ],
      "discriminating_test": {
        "description": "Within EDH, stratify records by bibliographic source, corpus, entry batch, editor, or record-creation/update metadata where available. Recompute provincial top-five concentration after removing the largest source corpora one at a time, equal-weighting source corpora, or testing whether top provinces are disproportionately supplied by a small number of sources.",
        "computable_on_held_data": true,
        "what_result_favors_rival": "The rival is favored if the holdout top-five share is mostly produced by a small number of sources or import batches, and falls substantially when source coverage is equalized; the stated mechanism is favored if concentration persists across independent sources and entry strata."
      }
    }
  ],
  "no_viable_rival": false,
  "notes": "With only province-level totals, these mechanisms cannot be adjudicated directly; they are proposed as discriminable rivals worth testing."
}
