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Record W4403987324 · doi:10.1016/j.actpsy.2024.104554

Feminist understandings of newcomer women's embodiment

2024· article· en· W4403987324 on OpenAlexaffabout
Amy Rose Green, Anusha Kassan, Farah Charania, Shelly Russell‐Mayhew, Suzanne Goopy

Bibliographic record

VenueActa Psychologica · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGender Roles and Identity Studies
Canadian institutionsUniversity of British ColumbiaUniversity of Calgary
Fundersnot available
KeywordsPsychologyCommunication

Abstract

fetched live from OpenAlex

In recent years, numerous scholars have advocated for the concept of embodiment—defined as the experience of engaging one's body with the world ( Allan, 2005 ; Piran & Teall, 2012 )—as a valuable framework for understanding women's experiences of their bodies. However, there is a paucity of research on embodiment specifically among newcomer women (including immigrants, refugees, and non-permanent residents) who belong to racialized groups in Canada. This article presents findings from a feminist research study employing an Arts-Based Engagement Ethnography (ABEE) methodology to investigate the embodiment experiences of six racialized newcomer women in Canada. The study reveals several unique factors influencing embodiment in this demographic, suggesting that future research, clinical practice, and social justice efforts should consider these factors both conceptually and methodologically. • Newcomer women view their bodies as multifaceted, integrating physical, mental, emotional, and spiritual dimensions. • They see their bodies relationally, with embodied experiences shaping and being shaped by their connections to others. • Spirituality nurtures a sense of wholenesss, connecting women to larger entities through art, music, and dance. • Sociocultural expectations affect how women percieve their bodies, shaped by societal and interpersonal influences. • Embodiment deepy impacts newcomer women's wellbeing influencing their integration into Canadian society across life areas.

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)0.000
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.475
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.063
GPT teacher head0.372
Teacher spread0.309 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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