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.
The abstract examines how human decision biases enter machine-learning pipelines and affect allocation fairness and platform outcomes in microlending.
Scope: abstract-level
The publisher issue materials frame this paper around the sources and evolution of bias across repeated human and algorithmic decisions.
Scope: publisher TOC preview abstract
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; full text was not inspected.
- The publisher surface was not queried after the lane’s quarantined dynamic-challenge response; no independent publisher-page verification was attempted.
- Publisher TOC preview abstract is truncated; full text was not inspected.
- Special-issue membership is established by the issue heading.
Source independence
publisher-only