---
conjecture: r3-b1-18
family: grok
model: "Grok 4.5 expert (chat paste-back via orchestrator window)"
received: 2026-08-06
template: PROMPT_TEMPLATE_v1.md sha256 4344aabfacfe88362c56d89b6c89d594a7bf3a221e18a16b0e351482447e512f
rivals_parsed: 2
---

{
  "rivals": [
    {
      "mechanism": "The higher top-1 shares in the single-city union territories are an artifact of the portal's administrative facet boundaries themselves: union-territory facets are defined more narrowly and therefore inherit fewer distinct institution entities by construction, automatically elevating the share of whichever single institution dominates the smaller pool, rather than any real structural difference in collecting landscape between single-city and multi-city units.",
      "why_it_explains_the_same_evidence": "Any administrative unit that the portal treats as a single-city UT will, by having a smaller absolute number of registered institutions, tend to show a higher top-1 share; this would produce the observed exceedances (51.47% and 100%) over the multi-city training maximum of 25.49% without requiring a genuine narrower landscape effect.",
      "named_confounds": ["administrative or geographic classification artifact", "unit-of-count or facet-boundary effect"],
      "discriminating_test": {
        "description": "Identify multi-city states that contain individual cities comparable in size or administrative character to the tested UTs; recompute top-1 institution share inside those single-city sub-regions (if the portal or external data allow city-level filtering) and compare against the UT shares and the state-level training maximum.",
        "computable_on_held_data": false,
        "what_result_favors_rival": "If single-city sub-regions inside large multi-city states also routinely exceed 25.49% top-1 share, this favors the rival (facet-size artifact); if single-city sub-regions inside multi-city states stay near or below the training maximum while true single-city UTs exceed it, this favors the proposed structural-narrower-landscape mechanism."
      }
    },
    {
      "mechanism": "The two tested single-city UTs happen to contain one or more historically dominant institutions (e.g., a major national or regional repository located in the capital city) that absorb the bulk of holdings for reasons of historical centralization, not because single-city units in general have narrower landscapes.",
      "why_it_explains_the_same_evidence": "If the particular UTs that landed first simply house outsized institutions by historical accident, their top-1 shares will exceed the multi-city training maximum, matching the observed 51.47% and 100% outcomes, while other single-city units without such dominant institutions might not.",
      "named_confounds": ["selection effects in which UTs were tested", "historical centralization of major repositories in capital cities"],
      "discriminating_test": {
        "description": "Examine the identity and type of the top-1 institution in each tested UT and in the training states; also test any additional single-city or small administrative units that land later. Measure whether high top-1 shares are confined to UTs that contain a known national-level repository versus appearing in all small single-city units.",
        "computable_on_held_data": true,
        "what_result_favors_rival": "If the extreme top-1 shares are driven exclusively by the presence of a national or capital-city mega-institution and later small units without such institutions fall below the 25.49% threshold, this favors the rival; if every small single-city unit exceeds the threshold regardless of institution type, this favors the proposed general narrower-landscape mechanism."
      }
    }
  ],
  "no_viable_rival": false,
  "notes": ""
}
