Files
markitect-main/examples/infospace-with-history/output/evaluations/bank_risk_management.md
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

3.4 KiB

entity_slug, evaluator, evaluated_at, overall_score, scores
entity_slug evaluator evaluated_at overall_score scores
bank_risk_management null 2026-02-23T00:49:54.512788 4.0
name value max_value rationale
definition_precision 4.0 5.0 The definition clearly identifies bank risk management as practices and systems for identifying, assessing, and controlling specific types of risks (credit, liquidity, operational). It captures a distinct operational concept rather than being vague, though it could be slightly more precise about the mechanisms involved.
name value max_value rationale
source_grounding 2.0 5.0 While Smith discusses banking practices in Book II, Chapter 2, the modern terminology of "risk management" as a systematic discipline with categorized risk types (credit, liquidity, operational) reflects contemporary banking concepts that likely exceed what Smith explicitly articulated in 1776.
name value max_value rationale
domain_placement 5.0 5.0 The "Regulation" domain assignment is highly appropriate, as bank risk management is fundamentally about internal regulatory practices and controls that banks implement to maintain stability and comply with prudential requirements.
name value max_value rationale
vsm_relevance 5.0 5.0 This entity maps excellently to S3 (internal regulation/audit) as it represents the internal control and monitoring systems that banks use to regulate their own operations and maintain viability within the larger economic system.
name value max_value rationale
explanatory_value 4.0 5.0 The entity illuminates important structural mechanisms by which banks maintain stability and serve economic functions, explaining how financial institutions manage inherent uncertainties. It reveals operational processes rather than merely naming surface phenomena.

Evaluation: Bank Risk Management

definition_precision — 4.0 / 5.0

The definition clearly identifies bank risk management as practices and systems for identifying, assessing, and controlling specific types of risks (credit, liquidity, operational). It captures a distinct operational concept rather than being vague, though it could be slightly more precise about the mechanisms involved.

source_grounding — 2.0 / 5.0

While Smith discusses banking practices in Book II, Chapter 2, the modern terminology of "risk management" as a systematic discipline with categorized risk types (credit, liquidity, operational) reflects contemporary banking concepts that likely exceed what Smith explicitly articulated in 1776.

domain_placement — 5.0 / 5.0

The "Regulation" domain assignment is highly appropriate, as bank risk management is fundamentally about internal regulatory practices and controls that banks implement to maintain stability and comply with prudential requirements.

vsm_relevance — 5.0 / 5.0

This entity maps excellently to S3 (internal regulation/audit) as it represents the internal control and monitoring systems that banks use to regulate their own operations and maintain viability within the larger economic system.

explanatory_value — 4.0 / 5.0

The entity illuminates important structural mechanisms by which banks maintain stability and serve economic functions, explaining how financial institutions manage inherent uncertainties. It reveals operational processes rather than merely naming surface phenomena.