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Record W1935085905 · doi:10.17169/fqs-1.2.1098

Qualitative Research in Canadian Psychology

2008· article· en· W1935085905 on OpenAlexaffabout
David L. Rennie, Kimberly D. Watson, Althea M. Monteiro

Bibliographic record

VenueForum: Qualitative Social Research (Freie Universität Berlin) · 2008
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsYork University
Fundersnot available
KeywordsQualitative researchPsychologySociologySocial science

Abstract

fetched live from OpenAlex

In response to the first author's e-mailed depiction of his situation as a qualitative researcher in a large Canadian department of psychology, Canadian qualitative researchers in several disciplines were invited to respond to questions about their situations. A thematic analysis of the replies revealed that psychologists in departments affiliated with the faculties of arts and science operate in greater isolation than do those with affiliated with a faculty of education. The analysis also indicated that the use of qualitative research in psychology lags behind its uptake in the other disciplines with which it was compared. Themes in terms of responsiveness to the needs of graduate students, departmental and institutional support, funding and scholarship are presented and discussed. URN: urn:nbn:de:0114-fqs0002295

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)0.071
metaresearch head score (Gemma)0.068
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.929
Threshold uncertainty score0.949

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0710.068
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0100.020
Science and technology studies0.0380.016
Scholarly communication0.0090.003
Open science0.0030.012
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0160.001

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 head0.786
GPT teacher head0.740
Teacher spread0.045 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
DomainMethods
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

Citations12
Published2008
Admission routes2
Has abstractyes

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