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Paper Citation Record · LEDGER

Algorithm as Experiment: Machine Learning, Market Design, and Policy Eligibility Rules

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2104.12909.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2104.12909 v6

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:59:02.743841Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-07-09T00:15:47.438665Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 87d07153-ddf9-4552-813e-115dcc6ed723 · inbound

Regression discontinuity aggregation, with an application to the union effects on inequality cites this paper.

Regression discontinuity aggregation, with an application to the union effects on inequality Algorithm as Experiment: Machine Learning, Market Design, and Policy Eligibility Rules

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-10T22:59:02.743841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:59:02.743841Z digest=sha256:31e39dc924b26fe3eb0f57ce53da725a627cc0dfd812a3b53b72572c2d2837f4

Observation 3dd778b3-44b5-4726-b33b-6eba046f9f1a · inbound

Estimating Causal Effects from Data Generated by Stochastic Algorithms cites this paper.

Estimating Causal Effects from Data Generated by Stochastic Algorithms Algorithm as Experiment: Machine Learning, Market Design, and Policy Eligibility Rules

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-07-09T00:15:47.440648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-07-09T00:15:30.364680Z digest=sha256:e75fcaef8738418dadda3a38cc54f88b79f42bba383b38425ac9d41517c9c6e9