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Record W2095723554 · doi:10.1111/medu.12546

Seeing the ‘black box’ differently: assessor cognition from three research perspectives

2014· article· en· W2095723554 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMedical Education · 2014
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of Northern British Columbia
FundersAcademy of Medical Sciences
KeywordsCognitionContext (archaeology)PsychologyPerspective (graphical)InferenceField (mathematics)Cognitive psychologyApplied psychologyCognitive interviewSocial psychologyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

CONTEXT: Performance assessments, such as workplace-based assessments (WBAs), represent a crucial component of assessment strategy in medical education. Persistent concerns about rater variability in performance assessments have resulted in a new field of study focusing on the cognitive processes used by raters, or more inclusively, by assessors. METHODS: An international group of researchers met regularly to share and critique key findings in assessor cognition research. Through iterative discussions, they identified the prevailing approaches to assessor cognition research and noted that each of them were based on nearly disparate theoretical frameworks and literatures. This paper aims to provide a conceptual review of the different perspectives used by researchers in this field using the specific example of WBA. RESULTS: Three distinct, but not mutually exclusive, perspectives on the origins and possible solutions to variability in assessment judgements emerged from the discussions within the group of researchers: (i) the assessor as trainable: assessors vary because they do not apply assessment criteria correctly, use varied frames of reference and make unjustified inferences; (ii) the assessor as fallible: variations arise as a result of fundamental limitations in human cognition that mean assessors are readily and haphazardly influenced by their immediate context, and (iii) the assessor as meaningfully idiosyncratic: experts are capable of making sense of highly complex and nuanced scenarios through inference and contextual sensitivity, which suggests assessor differences may represent legitimate experience-based interpretations. CONCLUSIONS: Although each of the perspectives discussed in this paper advances our understanding of assessor cognition and its impact on WBA, every perspective has its limitations. Following a discussion of areas of concordance and discordance across the perspectives, we propose a coexistent view in which researchers and practitioners utilise aspects of all three perspectives with the goal of advancing assessment quality and ultimately improving patient care.

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)0.003
metaresearch head score (Gemma)0.033
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.676
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.033
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.042
GPT teacher head0.427
Teacher spread0.385 · 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