MétaCan
Menu
Back to cohort
Record W1586663622 · doi:10.1177/070674370705201206

Using Publication Statistics for Evaluation in Academic Psychiatry

2007· article· en· W1586663622 on OpenAlexafffundvenue
Robert Maunder

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2007
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsUniversity of Toronto
FundersSchool of Medicine, Stanford UniversityUniversity of Toronto
KeywordsCitationPublicationStatisticsPercentile rankRank (graph theory)PercentilePsychologyBibliometricsCitation analysisMedicineMedical educationLibrary scienceComputer scienceMathematicsPolitical science

Abstract

fetched live from OpenAlex

OBJECTIVE: The validity of using publication statistics to evaluate university faculty is not established. This study aimed to determine if publication statistics vary among psychiatric faculty members of different academic rank and if there are biases among disciplines. METHOD: Using the 10 most recent publications written by psychiatric faculty members at 2 schools of medicine, we compared the time to publish 10 papers, the 5-year impact, the citation rate, and the citation ratio according to academic rank and school. Leaders in neuroscience were compared with leaders in clinical subspecialties. RESULTS: All statistics were associated with academic rank (P < or = 0.001) and there were significant differences between the 2 schools. There were more basic scientists than clinical subspecialists in the 80th percentile for 5-year impact (P = 0.04), but the latter disciplines performed equally in citation ratio. CONCLUSIONS: Publication statistics differ among academic ranks. Citation ratio minimizes the effect of biases among disciplines. Publication statistics may provide useful information for evaluating psychiatric faculty.

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)0.012
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.486
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.239
GPT teacher head0.506
Teacher spread0.266 · 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.

Study designObservational
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

Citations14
Published2007
Admission routes3
Has abstractyes

Explore more

Same venueThe Canadian Journal of PsychiatrySame topicHealth and Medical Research ImpactsFrench-language works237,207