Evidence map›Paper›PMID 40546318›Full record

ArticleSynthese2025

Fairness and randomness in decision-making: the case of decision thresholds.

Kate Vredenburgh

Abstract read
In one paragraph

Article in Synthese, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Kate VredenburghDepartment of Philosophy, Logic, and Scientific Method, LSE, London, England.ORCID 0000-0001-5721-5609

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper defends the role of lotteries in fair decision-making. It does so by targeting the use of decision thresholds to convert algorithmic predictions and classifications into decisions. Using an account of fairness from John Broome, the paper argues that decision thresholds are sometimes unfair, and that lotteries would be a fairer allocation method. It closes by dealing with two objections. First, it deals with the objection that lotteries should only be used to break ties in cases where individuals' claims are equally strong. Here, the paper gives a new argument for Broome's view, targeting decision criteria that are arbitrary and highly standardized. It then defends the arguments of the paper against the objection that lotteries are not morally superior to other methods of arbitrary choosing.

Indexed as

AIAlgorithmic decision-makingFairnessRandomness

Identifiers

PMID40546318
PMCPMC12177002

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.