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Record W2004398341 · doi:10.1080/095150700300091820

Reviewing effective components of feminist therapy

2000· article· en· W2004398341 on OpenAlexafffund
Anne Lea Israeli, Darcy A. Santor

Bibliographic record

VenueCounselling Psychology Quarterly · 2000
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsCentre for Addiction and Mental Health
FundersSocial Sciences and Humanities Research Council of CanadaDalhousie UniversityCentre for Addiction and Mental Health
KeywordsResocializationPsychotherapistCore (optical fiber)ConsciousnessSociologyPsychologySocial scienceComputer science

Abstract

fetched live from OpenAlex

Despite the broad application of feminist techniques and advances in defining feminist theory for psychological practice, consensus regarding the effectiveness of core components and techniques specific to feminist therapy is still evolving. This paper identifies four core components of feminist therapy: consciousness raising, social and gender role analysis, resocialization and social activism, and evaluates existing research evaluating their therapeutic effectiveness. Research to date suggests that many of these core components are promising. Future research on each of these key components is proposed.

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)0.013
metaresearch head score (Gemma)0.030
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: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.030
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0110.006
Science and technology studies0.0030.005
Scholarly communication0.0050.006
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.042
GPT teacher head0.376
Teacher spread0.334 · 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
GenreReview

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

Citations58
Published2000
Admission routes2
Has abstractyes

Explore more

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