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Record W3132003272 · doi:10.1177/0959353521989537

Editorial introduction: The politics of psychological suffering

2021· editorial· en· W3132003272 on OpenAlex
Jeanne Marecek, Michelle N. Lafrance

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFeminism & Psychology · 2021
Typeeditorial
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsSt. Thomas University
Fundersnot available
KeywordsPoliticsPsychological traumaPsychologyMedical diagnosisPsychotherapistSociologyMedicinePolitical science

Abstract

fetched live from OpenAlex

This special issue, “The politics of psychological suffering,” draws attention to the contested bases of knowledge in the “psy” professions (psychiatry, psychology, psychotherapy and related disciplines) (Foucault, 1977; Rose, 1999). We aim to explore the political contexts and production of people’s psychological distress. We take “psychological suffering” as the starting point for analysis, as a means of dislodging prefigured notions of individualized “mental illness” or “psychopathology.” This, we hope, serves as a feminist counterpoint to mainstream understandings of psychological suffering as biomedical illness. Exploring a range of experiences (from women’s sexuality to eating difficulties to responses to traumatic events), the articles in this issue disrupt and re-envision the taken-for-granted ways in which the psy professions typically frame and engage with people’s pain.

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.

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), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.055
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.026
GPT teacher head0.406
Teacher spread0.380 · 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