W4383268591 Working papers AI × management and organizations

Algorithmic Management in Scientific Research

Maximilian Koehler · Henry Sauermann

Also recorded as: doi:10.2139/ssrn.4497871 · ssrn:4497871

ssrn abstract page · 2023-07-05

Recorded claims
1
coded from the inspected source
Evidence classes
1
ssrn-abstract-page
Recorded limitations
2
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.

In crowd science, the abstract identifies algorithmic-management applications in five organizational functions: task division and allocation, direction, coordination, motivation, and support for learning.

confidence: high ssrn-abstract-page apw-e1-ssrn-backfill

Scope: Crowd-science projects and human research contributors; project and interview counts are not reported on the abstract page

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 evidence only; full text and PDFs were not inspected.
  • The abstract reports project comparisons and interviews but gives no project, interview, or participant denominators, sampling frame, observation period, coding procedure, effect sizes, or uncertainty measures; the comparisons should not be read causally.

Source independence

ssrn-only