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Anxious solidarities against the mental health crisis: connecting personal struggles to wider social and economic injustices

2023· article· en· W4386881389 on OpenAlexaff
A.T. Kingsmith

Bibliographic record

VenueGlobal Political Economy · 2023
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsOntario College of Art and Design
Fundersnot available
KeywordsSolidarityMental healthStatus quoFeelingFraming (construction)AnxietySociologyPolitical economySocial psychologyPolitical sciencePsychologyPoliticsPsychotherapistPsychiatryLawHistory

Abstract

fetched live from OpenAlex

Rates of anxiety have been steadily increasing over the past 20 years, prompting commentators to warn that we are in the throes of a global mental health crisis that is ruining well-being, threatening lives and damaging the economy. By highlighting how a person’s mental health, while nuanced and distinct, is always situated in a larger socio-emotional context or ‘structure of feeling’, this article argues that the issue of rising anxiety is a direct consequence of a biomedical model of treatment and care beholden to a neoliberal economic system that objectifies and isolates people. Through a framework termed ‘liberation health modelling’, it explores the progressive potential of ‘anxious solidarities’ as a way to reframe the problem of anxiety by connecting personal struggles to wider social and economic injustices. At a time when it is becoming impossible to deny the collective and widespread nature of people’s anxieties, the point of anxious solidarity is not simply to recount pain and suffering but to ‘make sense’ of it in relation to overarching structures of social oppression – calling into question the status quo in solidarity with other subjugated groups. Since struggles with anxiety have the advantage of being familiar to most, anyone can be a potential provocateur so long as they disavow an entirely personalised framing of their mental health.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.672
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.134
GPT teacher head0.432
Teacher spread0.298 · 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.

Study designTheoretical or conceptual
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

Citations1
Published2023
Admission routes1
Has abstractyes

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