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Record W4400578362 · doi:10.12957/bjhbs.2024.85281

The dynamic of intersected social categories in social interactions in a Brazilian psychosocial care center

2024· article· en· W4400578362 on OpenAlexaff
Roberta Soares

Bibliographic record

VenueBrazilian Journal of Health and Biomedical Sciences · 2024
Typearticle
Languageen
FieldPsychology
TopicSocial Representations and Identity
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPsychosocialCenter (category theory)Social carePsychologySociologyMedicineNursingPsychotherapist

Abstract

fetched live from OpenAlex

The Brazilian Psychiatric Reform advocates non-asylum treatment for individuals diagnosed with severe or persistent mental disorders, which is conducted mainly by Psychosocial Care Centers. This study aims to understand the role of intersected social categories in social interactions among social actors in those institutions. This qualitative ethnographic research uses the technique of participant observation. For the theoretical framework, intersectionality theory was chosen, in combination with the concept of intersectional stigma to reflect on intersectional discrimination. Erving Goffman´s works are also used to evaluate how social categories are socially situated. In addition to power relations between staff members and patients, the study examined the intersection of social categories, including how the social actors involved tend to notice their oppressions, but not their privileges, that is, the oppressions of others. The researcher argues therefore that, within that institution, the intersected social categories influence the dynamic of social interactions and generate an even more unjust experience for the patients in the institution in question.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.702
Threshold uncertainty score0.447

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.029
GPT teacher head0.432
Teacher spread0.403 · 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 designObservational
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 routes1
Has abstractyes

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