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Record W2020225838 · doi:10.1177/0886109903257550

Focus-Group Methodology in Research with Incarcerated Women: Race, Power, and Collective Experience

2003· article· en· W2020225838 on OpenAlexaffabout
Shoshana Pollack

Bibliographic record

VenueAffilia · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicFocus Groups and Qualitative Methods
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsOppressionFocus groupGender studiesSociologyRace (biology)IndividualismHuman sexualityPower (physics)Social psychologyPsychologyPolitical sciencePolitics

Abstract

fetched live from OpenAlex

Feminist researchers have found focus groups to be valuable for understanding collective experiences of marginalization, developing a structural analysis of individual experiences, and challenging taken-for-granted assumptions about race, gender, sexuality, and class. These benefits are in contrast to individual interviews, which may lend themselves to privatized and individualistic accounts of gendered experiences and which risk reproducing colonizing relationships and discourses. This study used both individual interviews (life-history methodology) and focus-group interviews to examine the effects of marginalization and oppression on Black Canadian women's lawbreaking. Combining these two methodologies may be particularly fruitful in cross-cultural and/or cross-racial research and in contexts such as correctional institutions, where issues of power and disclosure are amplified.

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)0.056
metaresearch head score (Gemma)0.031
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 score0.056
Threshold uncertainty score0.298

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0560.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.004
Science and technology studies0.0090.011
Scholarly communication0.0030.003
Open science0.0020.005
Research integrity0.0020.001
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 head0.322
GPT teacher head0.515
Teacher spread0.193 · 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

Citations72
Published2003
Admission routes2
Has abstractyes

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