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Record W1812522816 · doi:10.47678/cjhe.v27i2/3.183305

Pitfalls in the Assessment of Postgraduate Scholarship Programs: The Need for New Indicators

2017· article· en· W1812522816 on OpenAlexaffvenueabout
France Dussault, André Manseau

Bibliographic record

VenueCanadian Journal of Higher Education · 2017
Typearticle
Languageen
FieldHealth Professions
TopicDoctoral Education Challenges and Solutions
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsScholarshipVariety (cybernetics)SociologyPsychologyMedical educationPolitical scienceMedicineStatisticsMathematics

Abstract

fetched live from OpenAlex

Very few published studies have examined the outcomes of postgraduate scholarship programs. Basing our analysis on these studies and on internal reports from U.S. and Canadian organizations involved in scholarship programs, we have compiled an overview of the wide variety of indicators and methods that have been used, and conducted a comparative study of outcomes using the four most commonly used indicators: awarded diploma, obtained job, obtained related job, and pursuing studies. Our analysis revealed several methodological pitfalls in comparing the results. Although the use of available data limits the depth of a comparative analysis, our results show that scholarship programs tend to increase the rate of awarded diplomas.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.460
metaresearch head score (Gemma)0.639
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.990
Threshold uncertainty score0.665

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4600.639
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0320.038
Science and technology studies0.0040.009
Scholarly communication0.0150.025
Open science0.0080.011
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0020.001

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 head0.285
GPT teacher head0.568
Teacher spread0.283 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designTheoretical or conceptual
DomainEvaluation
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

Citations0
Published2017
Admission routes3
Has abstractyes

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