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Record W4412469144 · doi:10.1027/1866-5888/a000371

Comparing Ratee Reactions to the Relative Percentile Method and the Graphic Rating Scale

2025· article· en· W4412469144 on OpenAlexaff
Kabir N. Daljeet, Justin R. Feeney, Richard D. Goffin, Kevin Doyle

Bibliographic record

VenueJournal of Personnel Psychology · 2025
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsCanada Auto WorkersWestern UniversityUniversité de Montréal
Fundersnot available
KeywordsRating scalePercentileScale (ratio)PsychologySocial psychologyApplied psychologyStatisticsEconometricsMathematicsDevelopmental psychologyCartographyGeography

Abstract

fetched live from OpenAlex

Abstract: We examined how reactions to the Relative Percentile Method (RPM, a social comparative method) and the Graphic Rating Scale (GRS, an absolute performance rating method) influenced ratee feedback reactions, including perceptions of accuracy, fairness, clarity, self-awareness, and their intentions to use the feedback. We recruited 311 participants online and randomly assigned them to receive either social-comparative or absolute performance feedback in an exercise where they were asked to take on the role of an employee receiving feedback. Participants acting as ratees who received social-comparative feedback via the RPM reported significantly greater self-awareness and intention to use the feedback than ratees who received absolute feedback via the GRS. The implications and future directions are discussed.

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.

How this classification was reachedexpand

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.871
Threshold uncertainty score0.247

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.312
Teacher spread0.290 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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