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Record W4416275040 · doi:10.1080/13645579.2025.2590501

Thinking through country-as-culture qualitative sampling

2025· article· en· W4416275040 on OpenAlexafffundabout
KelleyAnne Malinen, Karen Kennedy

Bibliographic record

VenueInternational Journal of Social Research Methodology · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsCape Breton UniversityMount Saint Vincent University
FundersSocial Sciences and Humanities Research Council of CanadaMount Saint Vincent University
KeywordsQualitative researchSampling (signal processing)Data collectionResearch methodologyScale (ratio)Probability sampling

Abstract

fetched live from OpenAlex

Culture and Perspectives on Sexual Assault Policy was a qualitative, focus-group study that deployed nationally and regionally defined samples of domestic and international students in Nova Scotia, Canada. The objective was to produce recommendations for culturally relevant university sexual violence policies and responses. We contribute to discussions about methodological advantages and disadvantages of country-as-culture sampling, suggesting the following: 1) National/regional sampling strategies may be particularly well suited to research topics impacted by national and international structures. 2) Resonance of national and/or regional categories among participants during qualitative data collection may validate this sampling strategy. 3) Researchers can offset stereotyping by highlighting perspectival heterogeneity within sampled groups. 4) Country as culture sampling may be complimented by strategies that engage other axes of identity. We suggest three such approaches: stakeholder consultations to identify additional groups relevant to the study, follow-up questionnaires and/or interviews, and reflection about groups that have not been included.

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)0.120
metaresearch head score (Gemma)0.084
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.880
Threshold uncertainty score0.632

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1200.084
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0080.010
Scholarly communication0.0070.006
Open science0.0030.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.783
GPT teacher head0.772
Teacher spread0.011 · 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 designTheoretical or conceptual
DomainMethods
GenreMethods

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
Published2025
Admission routes3
Has abstractyes

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