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Record W2044749336 · doi:10.1152/advan.00071.2009

Teaching undergraduates the process of peer review: learning by doing

2010· article· en· W2044749336 on OpenAlexafffund
P. K. Rangachari

Bibliographic record

VenueAJP Advances in Physiology Education · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicWikis in Education and Collaboration
Canadian institutionsMcMaster University
FundersMcMaster UniversityUniversity of Calgary
KeywordsInterimMedical educationPeer reviewPsychologyPeer feedbackProcess (computing)Peer evaluationMathematics educationMedicineHigher educationComputer science

Abstract

fetched live from OpenAlex

An active approach allowed undergraduates in Health Sciences to learn the dynamics of peer review at first hand. A four-stage process was used. In stage 1, students formed self-selected groups to explore specific issues. In stage 2, each group posted their interim reports online on a specific date. Each student read all the other reports and prepared detailed critiques. In stage 3, each report was discussed at sessions where the lead discussant was selected at random. All students participated in the peer review process. The written critiques were collated and returned to each group, who were asked to resubmit their revised reports within 2 wk. In stage 4, final submissions accompanied by rebuttals were graded. Student responses to a questionnaire were highly positive. They recognized the individual steps in the standard peer review, appreciated the complexities involved, and got a first-hand experience of some of the inherent variabilities involved. The absence of formal presentations and the opportunity to read each other's reports permitted them to study issues in greater depth.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.887
Threshold uncertainty score0.291

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 integrity0.0000.000
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 head0.006
GPT teacher head0.382
Teacher spread0.376 · 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 designNot applicable
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

Citations20
Published2010
Admission routes2
Has abstractyes

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