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Record W4404814014 · doi:10.15210/rps.v10i01.26902

ASPECTOS SOCIOPOLÍTICOS DO SOFRIMENTO PSÍQUICO

2024· article· pt· W4404814014 on OpenAlexaboutno aff
Amanda Karol de Oliveira Costa

Bibliographic record

VenuePerspectivas Sociais · 2024
Typearticle
Languagept
FieldPsychology
TopicPsychology and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyMedicine

Abstract

fetched live from OpenAlex

Este artigo pretende discutir os aspectos sociopolíticos do sofrimento psíquico e as estratégias políticas e ideológicas utilizadas pelo neoliberalismo para gerenciar o sofrimento psicossocial na contemporaneidade. Para tanto é desenvolvido estudo de natureza qualitativa e de caráter bibliográfico, cujas principais obras analisadas são dos autores: Dardot e Laval; Fisher; Martín-Baró; Gouveia, Amarantes e Freitas. A partir desse estudo, foi possível concluir que os condicionantes socioculturais do neoliberalismo implicam diretamente na construção das subjetividades e na produção social do sofrimento psíquico. Podendo dar novas configurações às expressões de sofrimento psicossocial, inclusive, ampliá-las e/ou intensificá-las. Tendo em vista que o individualismo, a competitividade, consumismo e constituição do indivíduo-empresa, são capazes de acentuar sentimentos e vivências de autoculpabilização, autocoerção; gerar angústia, frustração, desesperança, cansaço, estresse, etc. Também, compreende-se que a gerência neoliberal sobre o sofrimento psíquico envolve a psicologização, patologização, e medicalização. Estratégias úteis para o capital à medida que favorece o controle ideológico ao responsabilizar os sujeitos, ignorando as contradições sociais que perpassam a experiência individual. Também, de modo simultâneo, é vantajoso economicamente ao produzir lucros para as indústrias que comercializam o cuidado em saúde mental.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.805
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0310.027

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 head0.041
GPT teacher head0.435
Teacher spread0.394 · 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; both teacher heads agree on what is shown here.

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 routes1
Has abstractyes

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