Claim

The NBER paper says AI agents may dramatically reduce several transaction costs and create new market frictions; its listed authors and abstract do not establish the specific MIT-and-Harvard attribution or that transactions become literally nearly free.

Type OBSERVATIONAL · truth-evaluable: yes · status at snapshot: ACTIVE · created seq 7834

36 words; atomic claims are usually under 25a conjunction joins clauses that may be separately evaluable

Referenced 84 times: checked 0, looked up by assistants 0, viewed 84, shared 0. A count of attention, not evidence.

Topics

Not filed under any topic yet.

Assessment

Supported

Score: 0.8581 under ledger-default@0.3.0 at snapshot 27745

3 of 4 review checks done · 1 counted · 2 by the author only

1 independent evidence lineage · review checks 1 of 4 · stability MEDIUM

Main unresolved issue: 1 counted evidence item has no independence review; repeats of one origin may be counted as several coverage:06ff3afe-353d-8cf7-9452-e1914b63b6e8

Not yet independently audited.Evidence reviewed so far supports this claim, but only 1 of 4 review checks has been done.

Related: NARROWS outgoing: Supported

Why?

Strongest counted support: The NBER page attributes the paper to its listed authors and states that agents can reduce transaction costs while introducing frictions; it does not establish the specific MIT-and-Harvard attribution or literal near-zero transaction costs. weight 1.800000 evidence

Review gaps: qualifiers reviewed, opposing search done, independence reviewed

What would most change this: One independent, direct measurement that contradicts this claim would move it from Supported to Unresolved.

Hide calculation

0.8581 under ledger-default@0.3.0 at snapshot 27745 · state Supported · Review checks: 1 of 4 · stability MEDIUM · 1 source, 1 independent lineage

Model ledger-default@0.3.0 (the default model, not the answer) · snapshot 27745 · trace sha256:0b30bbd761f2b07ef8d34ec40c7285d3c0fc535f71bdc423d1643318d6ff85b5

Last changed at entry seq 8639; nothing logged since has borne on this claim.

How the number was reached

Each counted link is weighed by multiplying the factors the model declares; a factor it does not declare is not shown. Every factor name below links to what that number means.

Link	Working	Weight	Counted as
d5bf71be support	relevance DIRECT 2.0 × observation DIRECT_TEXT 0.9 × interpretation 0 steps, 1 − 0.15 × 0 1.000000 × authenticity UNVERIFIED 1.0 × extraction UNVERIFIED 1.0 × provenance INDEPENDENT 1.0 × edition NAMED_OR_UNRELATED 1	1.800000	1.800000

prior 0.50 → log-odds 0.000000 + 1.800000 (the counted weights) = 1.800000 → probability 0.8581

Under neighbouring settings of the same model: 0.7790 to 0.9121, a spread of 0.1331.

Half-even rounding, six places for weights and four for the probability. The same inputs under the same model reproduce this exactly; that is what the trace hash above is for. How a score is worked out explains every factor, why it is there, and what the model sets it to.

Your view

Registered views

Nobody has registered a view yet.

Registered views are personal belief, not evidence: they never change Galedra's assessment. Affiliations are self-declared and shown only for groups of 5 or more.

Evidence for

The NBER page attributes the paper to its listed authors and states that agents can reduce transaction costs while introducing frictions; it does not establish the specific MIT-and-Harvard attribution or literal near-zero transaction costs.

From The Coasean Singularity? Demand, Supply, and Market Design with AI Agents Read 2026-09-28 Relevance DIRECT Steps 0 Counted

Evidence against

None.

Qualifications

None.

Suppressed as dependent

None.

Inferences

Concluded from

None.

Used as a premise in

None.

An inference is interpretation, not evidence: it never changes the assessment of its conclusion. Each premise is a claim with its own evidence.

Threads

None. Threads are for disagreements about how a determination was made — a statement whose figures are not in the passage it rests on, two sources that may share an origin. Something about the world belongs in the evidence above.

Claim edges

From	Relationship	To
4b63b6e8	NARROWS	eae716f8

Review checklist

Review checks: 1 of 4

2 checks by this claim's own author, alongside the independent review above. 1 OPPOSING EVIDENCE SEARCH · 1 QUALIFIER CHECK. A check by the person who recorded a claim does not raise its review coverage.

Check	Done	By
qualifiers reviewed	no
opposing search done	no
independence reviewed	no
primary source reviewed	yes	d5bf71be

Summary

Supported. The main support is: The NBER page attributes the paper to its listed authors and states that agents can reduce transaction costs while introducing frictions; it does not establish the specific MIT-and-Harvard attribution or literal near-zero transaction costs. 5c7fe166

A search for evidence in the opposing direction found something; see the counted evidence. 4ee93234

Review checks: 1 of 4. coverage:06ff3afe-353d-8cf7-9452-e1914b63b6e8

Generated by stub-v0.1; every sentence cites graph ids.

Contribution history

seq	event	detail
7834	APPENDED
7835	ACCEPT	AUTOMATIC_AFTER_VALIDATION
8638	TASK_RESULT	by 1efd24fe (accepted)

Score trace

{
  "claim": "06ff3afe-353d-8cf7-9452-e1914b63b6e8",
  "links": [
    {
      "link": "fed26622-6313-8c64-8490-9947d5bf71be",
      "group": null,
      "edition": "NAMED_OR_UNRELATED",
      "evidence": "9c3a9a60-2711-8297-b54c-475b5c7fe166",
      "direction": "SUPPORT",
      "magnitude": "1.800000",
      "relevance": "DIRECT",
      "extraction": "UNVERIFIED",
      "provenance": "INDEPENDENT",
      "observation": "DIRECT_TEXT",
      "source_type": "PRIMARY_TEXT",
      "authenticity": "UNVERIFIED",
      "audit_confirmed": false,
      "effective_weight": "1.800000",
      "interpretive_steps": 0
    }
  ],
  "model": "ledger-default@0.3.0",
  "prior": "0.50",
  "variants": {
    "spread": "0.1331",
    "permissive": "0.9121",
    "conservative": "0.7790"
  },
  "code_hash": "sha256:c61a6fdf35a754a0d7e958df149036a083c0eaeb7d2d2e52704ec32b0c36def7",
  "contested": false,
  "stability": "MEDIUM",
  "claim_type": "OBSERVATIONAL",
  "config_hash": "sha256:86768038080b8ab5233f1e4b7aba10af05b5bb44caa432095150b90e81209809",
  "probability": "0.8581",
  "provisional": true,
  "evidence_sum": "1.800000",
  "snapshot_seq": 8639,
  "prior_log_odds": "0.000000",
  "support_groups": 1,
  "model_dependent": false,
  "review_coverage": "0.25",
  "truth_evaluable": true,
  "assessment_state": "SUPPORTED",
  "review_checklist": {
    "qualifiers_reviewed": {
      "by": [],
      "ok": false
    },
    "opposing_search_done": {
      "by": [],
      "ok": false
    },
    "independence_reviewed": {
      "by": [],
      "ok": false
    },
    "primary_source_reviewed": {
      "by": [
        "fed26622-6313-8c64-8490-9947d5bf71be"
      ],
      "ok": true
    }
  },
  "contradict_groups": 0,
  "rounding_boundary": false,
  "posterior_log_odds": "1.800000",
  "not_applicable_reason": null,
  "independence_unreviewed": 1
}