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tegwick a9ca0adfcf feat(example): add per-entity LLM evaluations for 985 WoN entities (S3.3)

Batch evaluation of all 988 entities via OpenRouter. 984 succeeded on
first pass; 3 failed (network errors). eval-summary --update-metrics
written with per_entity_mean=3.9556.

Viability dashboard: 6/6 PASS
  redundancy_ratio   0.0061  (max 0.10)
  coverage_ratio     0.6190  (min 0.40)
  coherence_comps    0.0000  (max 3)
  consistency_cycles 0.0000  (max 0)
  granularity_entropy 2.6748 (min 1.0)
  per_entity_mean    3.9556  (min 3.5)

Dimension breakdown (mean across 985 entities):
  definition_precision  3.62
  source_grounding      4.36
  domain_placement      4.56
  vsm_relevance         3.31
  explanatory_value     3.94

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

2026-02-23 09:36:46 +01:00

3.8 KiB

Raw Blame History

entity_slug, evaluator, evaluated_at, overall_score, scores

entity_slug

evaluator

evaluated_at

overall_score

scores

bank_information_asymmetry

null

2026-02-23T00:42:25.594624

4.0

name	value	max_value	rationale
definition_precision	4.0	5.0	The definition clearly articulates the concept of information asymmetry in banking contexts, distinguishing it from general market information problems. It specifies the parties involved (banks vs. other market participants) and the consequences (effects on credit allocation and risk assessment).

name	value	max_value	rationale
source_grounding	3.0	5.0	While Smith does discuss banking operations and credit assessment in Book II, Chapter 2, the specific framing of "information asymmetry" uses modern economic terminology that may not directly reflect Smith's 18th-century conceptual framework. The underlying ideas about banks' superior knowledge are present, but the theoretical construct is somewhat anachronistic.

name	value	max_value	rationale
domain_placement	5.0	5.0	The "Exchange" domain is perfectly appropriate for this concept, as information asymmetry fundamentally concerns how information flows (or fails to flow) between parties in financial transactions. This is a core aspect of exchange mechanisms and market functioning.

name	value	max_value	rationale
vsm_relevance	4.0	5.0	This entity maps well to S4 (intelligence/environmental adaptation) as it concerns how banks gather and process information about their environment to make lending decisions. It also relates to S3 (internal regulation) in terms of risk management processes that banks must implement to handle information gaps.

name	value	max_value	rationale
explanatory_value	4.0	5.0	The concept provides significant explanatory power for understanding banking mechanisms, credit markets, and financial intermediation. It illuminates why banks exist as specialized institutions and explains structural features of financial systems rather than merely describing surface phenomena.

Evaluation: Bank Information Asymmetry

definition_precision — 4.0 / 5.0

The definition clearly articulates the concept of information asymmetry in banking contexts, distinguishing it from general market information problems. It specifies the parties involved (banks vs. other market participants) and the consequences (effects on credit allocation and risk assessment).

source_grounding — 3.0 / 5.0

While Smith does discuss banking operations and credit assessment in Book II, Chapter 2, the specific framing of "information asymmetry" uses modern economic terminology that may not directly reflect Smith's 18th-century conceptual framework. The underlying ideas about banks' superior knowledge are present, but the theoretical construct is somewhat anachronistic.

domain_placement — 5.0 / 5.0

The "Exchange" domain is perfectly appropriate for this concept, as information asymmetry fundamentally concerns how information flows (or fails to flow) between parties in financial transactions. This is a core aspect of exchange mechanisms and market functioning.

vsm_relevance — 4.0 / 5.0

This entity maps well to S4 (intelligence/environmental adaptation) as it concerns how banks gather and process information about their environment to make lending decisions. It also relates to S3 (internal regulation) in terms of risk management processes that banks must implement to handle information gaps.

explanatory_value — 4.0 / 5.0

The concept provides significant explanatory power for understanding banking mechanisms, credit markets, and financial intermediation. It illuminates why banks exist as specialized institutions and explains structural features of financial systems rather than merely describing surface phenomena.

3.8 KiB Raw Blame History