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Record W2156470739 · doi:10.55016/ojs/ajer.v47i2.54856

Wheels Within Wheels: The Analysis of a Cultural Event

2001· article· en· W2156470739 on OpenAlexvenueno aff
Deborah Court

Bibliographic record

VenueAlberta Journal of Educational Research · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsnot available
Fundersnot available
KeywordsQualitative researchInclusion (mineral)Event (particle physics)PedagogySociologyDatabase transactionPsychologyQualitative analysisPositivismMathematics educationSocial psychologySocial sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

This article describes a one-semester course on qualitative research methods presented for faculty members in a university school of education. The course was one significant "cultural event" in an ongoing change process toward the inclusion of qualitative methods in a strongly positivistic setting. The inclusion of qualitative methods required a profound adjustment by participants in this culture. The change was eased by official sanction of the course and by faculty members' ability to find entry points to the ideas through established patterns of communication with the course presenters, most of whom came from within the faculty. The author is new to both the university and the country, and her own cultural adjustments, together with her role as one of the course presenters, leads her to reflect anew on the transaction between subjective and objective in qualitative research.

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)0.017
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.035
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.006
Science and technology studies0.0120.013
Scholarly communication0.0090.007
Open science0.0020.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.406
GPT teacher head0.631
Teacher spread0.225 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2001
Admission routes1
Has abstractyes

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