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Record W4232210518 · doi:10.15185/izalwol.48

http://wol.iza.org/articles/anonymous-job-applications-and-hiring-discrimination

2014· article· en· W4232210518 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueIZA World of Labor · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicNames, Identity, and Discrimination Research
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Anonymous job applications have the potential to remove or reduce some discriminatory hiring barriers facing applicants from minority and other disadvantaged groups.When implemented effectively, anonymous job applications level the playing field in access to jobs by shifting the focus toward skills and qualifications.Anonymous job applications should not, however, be regarded as a universal remedy that is applicable in any context or that can prevent any form of discrimination. ELEVATOR PITCHThe use of anonymous job applications (or blind recruitment) to combat hiring discrimination is gaining attention and interest.Results from field experiments and pilot projects in European countries (France, Germany, the Netherlands, and Sweden are considered here), Canada, and Australia shed light on their potential to reduce some of the discriminatory barriers to hiring for minority and other disadvantaged groups.But although this approach can achieve its primary aims, there are also important cautions to consider. KEY FINDINGS ConsAnonymous job applications have the potential to reduce discrimination only when discrimination is high.Anonymous job applications may simply postpone discrimination to later in the hiring process.Blind recruiting may foil other positive measures to promote more diversity and can limit the scope for affirmative action.Suboptimal implementation of anonymous job application procedures can be costly, timeconsuming, labor-intensive, and error-prone.Context-specific information may be interpreted disadvantageously if the candidate's identity is unknown. ProsAnonymous job applications can prevent discrimination in the initial screening stage of recruitment.Anonymous job applications may boost job offer rates for minority candidates.Anonymous job applications signal a strong employer commitment to focus solely on skills and qualifications.Standardized anonymous job application forms are an efficient implementation method.Job applicant comparability may increase with the use of anonymous job applications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.751
Threshold uncertainty score0.670

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.034
GPT teacher head0.353
Teacher spread0.319 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it