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Record W4385745016 · doi:10.59962/9780774820875

Feminist Community Research

2011· book· en· W4385745016 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of British Columbia Press eBooks · 2011
Typebook
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsnot available
Fundersnot available
KeywordsSociologyData scienceComputer science

Abstract

fetched live from OpenAlex

Feminist community research is a collaborative, policy-oriented methodology that holds the promise of empowering the disadvantaged and building a more just society. But in the absence of critical analysis and the responsible use of power, this approach can lead to naive or even harmful practices. Grounded as they are in fieldwork, these interdisciplinary case studies acknowledge the real methodological and ethical issues that researchers can encounter as they negotiate contested research relationships. The authors discuss the strategies – successful and unsuccessful – that they have employed to overcome these challenges. The authors’ collective experiences working with diverse groups, from immigrant and Aboriginal women in Vancouver to poverty-reduction practitioners in Vietnam, reveal that truly equitable research projects require that we question core concepts and address crucial issues such as the promises and limits of reflexivity; the politics of place, time, and resources; ethical dilemmas and emotional responses; and the way issues of social justice, policy, and social change are embedded in 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)0.006
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.068
Threshold uncertainty score0.226

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0080.008
Scholarly communication0.0050.003
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0680.009

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 head0.374
GPT teacher head0.437
Teacher spread0.063 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations21
Published2011
Admission routes1
Has abstractyes

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