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Record W4395471022 · doi:10.1007/978-3-031-52022-8_23

An Unanticipated Methodological Crisis: (Forced) Adaptations to Online Qualitative Methodological Encounters, Disruptions and Challenges During the COVID-19 Pandemic for Researching Marginalized Individuals on Gendered Islamophobia in Canada

2024· book-chapter· en· W4395471022 on OpenAlexaffabout
Arshia U. Zaidi

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicFocus Groups and Qualitative Methods
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsIslamophobiaCoronavirus disease 2019 (COVID-19)PandemicPolitical science2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)SociologyCriminologyGender studiesMedicineLawPoliticsVirology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.170
metaresearch head score (Gemma)0.162
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 score0.830
Threshold uncertainty score0.897

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1700.162
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0230.058
Scholarly communication0.0240.015
Open science0.0060.013
Research integrity0.0090.016
Insufficient payload (model declined to judge)0.0060.001

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 head0.766
GPT teacher head0.585
Teacher spread0.181 · 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

Citations0
Published2024
Admission routes2
Has abstractno

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