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Record W2337224714 · doi:10.1080/15426432.2015.1080605

Mindfulness based feminist therapy: The intermingling edges of self-compassion and social justice

2016· article· en· W2337224714 on OpenAlexaff
Rachael Crowder

Bibliographic record

VenueJournal of Religion & Spirituality in Social Work Social Thought · 2016
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsUniversity of LethbridgeUniversity of Calgary
Fundersnot available
KeywordsMindfulnessFeminismOppressionPsychologyAgency (philosophy)CompassionPostmodernismBuddhismPsychotherapistSociologyGender studiesSocial psychologyPoliticsEpistemologySocial sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

Survivors of intimate partner violence (IPV) often have trouble regaining a lost sense of self, even after years of ‘good’ feminist therapy. Both postmodern feminism and Buddhist philosophy have common ideas about the constructed nature and fluidity of the self, and feminist and Buddhist ontologies can inform each other—the former on the nature of subjectivity under oppression, the latter on how to relate differently to the self by not identifying with our stories as who we are. Therefore, one might assume that mindfulness-based approaches might be helpful with this problem. However, social justice values that feminists and social workers prize seem absent in mindfulness approaches that appear to be individual-focused and politically passive. This article argues that feminism and mindfulness have points of congruence as well as much to offer each other where they diverge, and it presents exploratory research investigating the role of mindfulness and self-compassion on reconstructing a sense of self and agency in survivors of IPV by comparing outcomes of a community-based feminist group and a mindfulness-based group. The findings provide a glimpse into the strengths of each approach and suggest some benefit in weaving these into a mindfulness based feminist therapy for survivors of IPV.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.488
Threshold uncertainty score0.819

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.043
GPT teacher head0.354
Teacher spread0.311 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations32
Published2016
Admission routes1
Has abstractyes

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