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Record W2967019446 · doi:10.1111/maq.12542

Identified Patient: Apartheid Syndrome, Political Therapeutics, and Generational Care in South Africa

2019· article· en· W2967019446 on OpenAlexfundno aff
Stephen McIsaac

Bibliographic record

VenueMedical Anthropology Quarterly · 2019
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaSocial Science Research Council
KeywordsPoliticsNormativeRacismColonialismEmbodied cognitionGender studiesSociologyCriminologyPolitical scienceLawEpistemology

Abstract

fetched live from OpenAlex

In contemporary South Africa, racism, economic exclusion, and spatial segregation remain trenchant features of everyday life 25 years after the end of apartheid. In this article, I show how therapeutic practices by black South Africans in one of the country's largest townships address the ongoing legacies of this history. Rather than treat individual psyches, therapists' practices are oriented toward the relational space between generations, a political therapeutic driven by the affective force of the therapists' own history of struggle toward a different future for black youth, who continue to be marked by the legacies of colonialism and apartheid. In the process, I track how this political therapeutic confronts the normative demands of psychiatric knowledge. Overall, I argue that rather than solely focusing on the violence of care in clinical settings, we should interrogate political generation and embodied history as forms of expertise and their constitutive potentialities.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.007
Scholarly communication0.0020.002
Open science0.0000.005
Research integrity0.0010.002
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 head0.075
GPT teacher head0.388
Teacher spread0.312 · 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 designQualitative
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

Citations3
Published2019
Admission routes1
Has abstractyes

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