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Record W2077380636 · doi:10.1037/a0015165

Rating formats and rater training redux: A context-specific approach for enhancing the effectiveness of performance management.

2009· article· en· W2077380636 on OpenAlex
Heather A. MacDonald, Lorne M. Sulsky

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Journal of Behavioural Science/Revue canadienne des sciences du comportement · 2009
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsReduxPsychologyApplied psychologyContext (archaeology)Medical education

Abstract

fetched live from OpenAlex

Dans cet article, nous procedons a l'examen critique des recherches anterieures sur les formats d'evaluation et l'entrainement des evaluateurs dans le contexte de la mesure des performances. Historiquement, le but de cette branche de recherche a ete de trouver des facons de maximiser les qualites psychometriques des donnees d'evaluation de la performance. Notre idee centrale est qu'il existe un certain nombre d'avenues pour elargir cette recherche. De fait, nous proposons un modele conceptuel qui pourrait servir de cadre conceptuel pour les travaux futurs portant sur ces deux questions de recherche traditionnelles en mesure de la performance. Par exemple, autant le format des evaluations que la formation des evaluateurs pourraient servir pour faciliter et ameliorer les retroactions et le processus de formation des employes ainsi que pour reduire les biais possibles dus a l'evaluateur. De plus, les recherches sur le format et l'entrainement pourraient permettre de trouver des facons de maximiser les reactions de l'evaluateur et de la personne evaluee au systeme de mesures. Une caracteristique centrale de notre modele est l'integration de la culture nationale comme variable moderatrice des relations entre des formats donnes, les programmes d'entrainement et differents resultats. Nous considerons autant la culture nationale de l'evaluateur que de la personne evaluee et nous portons une attention particuliere aux comparaisons entre les cultures asiatiques occidentale et orientale.

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)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.351
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.002
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.101
GPT teacher head0.276
Teacher spread0.176 · 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