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Record W2017593112 · doi:10.1080/10401334.2010.488205

Is Undergraduate Performance Predictive of Postgraduate Performance?

2010· article· en· W2017593112 on OpenAlex
Wayne Woloschuk, Kevin McLaughlin, Bruce Wright

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueTeaching and Learning in Medicine · 2010
Typearticle
Languageen
FieldMedicine
TopicMedical Education and Admissions
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedical educationPsychologyMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: The continuity of undergraduate to postgraduate training suggests that performance in medical school should predict performance later in residency. PURPOSE: The goal is to determine whether undergraduate performance is predictive of postgraduate performance. METHODS: Residency program directors assessed the performance of medical school graduates (Classes 2004-2006) at the end of the 1st postgraduate year. Measures of undergraduate performance were retrieved including grade point averages, clerkship in-training evaluation reports, and the total score on the Medical Council of Canada Part 1 exam. RESULTS: Complete data were available for 242 (81.5%) graduates. Postgraduate performance consisted of two reliable factors (clinical acumen and human sensitivity) that explained 78% of the variance. Correlations between undergraduate and the two postgraduate measures were low (.03-.31). CONCLUSIONS: Measures of undergraduate performance appear to be poor predictors of performance in residency that consisted of two primary dimensions (clinical acumen and human sensitivity).

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.238
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
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 integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.326
Teacher spread0.306 · 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