MétaCan
Menu
Back to cohort
Record W2998071621 · doi:10.1017/s1049096519001100

The Qualifying Field Exam: What Is It Good For?

2019· article· en· W2998071621 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePS Political Science & Politics · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Science Research and Education
Canadian institutionsWestern University
Fundersnot available
KeywordsTheme (computing)Group cohesivenessValue (mathematics)Field (mathematics)PoliticsCertificationSociologyVariety (cybernetics)EpistemologyPublic relationsPolitical sciencePsychologySocial psychologyComputer scienceLawWorld Wide WebMathematicsPhilosophyArtificial intelligence

Abstract

fetched live from OpenAlex

ABSTRACT Most political scientists self-identify as a comparativist, theorist, Americanist, or another label corresponding with the qualifying field exams (QFE) that they passed during their doctoral studies. Passing the QFE indicates that a graduate student or faculty member is broadly familiar with the full range of theories, approaches, and debates within a subfield or research theme. The value of the QFE as a form of certification, however, depends on the extent to which the subfield or theme is cohesive in and of itself as well as whether departmental lists draw on a common pool of publications. This article investigates the value of the QFE by examining the cohesiveness of 16 Canadian politics PhD QFE lists. Our findings suggest that it is problematic to assume that scholars who pass a QFE share a common knowledge base.

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)0.008
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.714
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.004
Scholarly communication0.0020.002
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.102
GPT teacher head0.481
Teacher spread0.379 · 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