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Record W2328777853 · doi:10.1177/1363461516635534

Postsocialism, the psy-ences and mental health

2016· review· en· W2328777853 on OpenAlexaff
Eugene Raikhel, Dörte Bemme

Bibliographic record

VenueTranscultural Psychiatry · 2016
Typereview
Languageen
FieldPsychology
TopicHistorical Psychiatry and Medical Practices
Canadian institutionsMcGill University
Fundersnot available
KeywordsMental healthPsychologyPsychiatryPsychotherapist

Abstract

fetched live from OpenAlex

Over the past decades, the formerly socialist countries of East Central Europe and Eurasia have experienced a range of transformations which bear directly upon the domains of mental health, psychiatry, and psychology. In particular, the disciplines and professions concerned with the human mind, brain, and behavior ("the psy-ences") were strongly affected by sociopolitical changes spanning the state-socialist and postsocialist periods. These disciplines' relationship to the state, their modes of knowledge production, and the epistemic order and subjectivities they contributed to have all undergone dramatic ruptures. In this essay, we trace the literature on these issues across three thematic domains: (a) history and memory; (b) the reform of psychiatry in an era of global mental health; and (c) therapy and self-fashioning. We argue for a closer articulation between the social science and historical literature on socialism and its "posts" and the literature among anthropologists, sociologists, and historians on the sciences of the mind and brain, and we suggest that each of these literatures helps to critically open up and enrich the other.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0010.004
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.058
GPT teacher head0.430
Teacher spread0.371 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations38
Published2016
Admission routes1
Has abstractyes

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