W7164583611 Peer-reviewed research AI × management and organizations

The AI Democratization Paradox: Evidence from Decentralized Knowledge Communities

Kai Zhu · Dylan Walker

Also recorded as: doi:10.1287/mnsc.2024.04717

Management Science · 2026-06-12

Recorded claims
1
coded from the inspected source
Evidence classes
1
crossref-api-metadata
Recorded limitations
3
stated, never hidden

From the hash-bound evidence releases

Recorded claims

Each claim states what the inspected source says, at the recorded location—bounded by its scope and graded by its confidence. Nothing here is a synthesis across works.

A natural-experiment study of decentralized Wikipedia language communities reports that neural machine translation increased content creation without reducing quality or readership, but gains were concentrated in better-resourced communities and remained constrained by existing social structure.

confidence: high crossref-api-metadata apw-c1-obot-journals

Scope: publisher-deposited abstract metadata; the abstract describes more than 100 language communities but does not provide an exact denominator or study period

Structured relationships

In-corpus citations

Only source-supplied cites relationships whose two endpoints are admitted are shown. Invocation evidence remains a separate relationship.

Cites (0)

No in-corpus outgoing citation is available in the current enrichment coverage.

Cited by (0)

No in-corpus incoming citation is available in the current enrichment coverage.

Boundaries

Limitations & independence

Recorded at coding time, carried with the work forever. A claim without its limits is not evidence.

Recorded limitations

  • Abstract-level Crossref metadata only; the publisher landing page could not be retained because public retrieval was access-blocked.
  • The abstract gives only an approximate community count and no study period; no numerical effect-size claim is carried forward.
  • Full text was not inspected.

Source independence

publisher-only