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Record W2939422990 · doi:10.18192/aporia.v11i2.4597

The social reproduction of difference: Mental illness and the intensive care environment

2020· article· en· W2939422990 on OpenAlexvenueno aff
Floraidh Corfee, Leonie Cox, Carol Windsor

Bibliographic record

VenueAporia · 2020
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsnot available
Fundersnot available
KeywordsIntensive carePsychosocialReproductionNursingPsychologyPower (physics)SociologyMedicinePsychiatryEcologyIntensive care medicine

Abstract

fetched live from OpenAlex

This paper uses social constructionism to critically explore the social world of intensive care units, and to consider how the presence of mental health consumers impacts on nursing practice. Following a series of interviews with intensive care nurses, our analysis suggested consumers are disenfranchised through stigma, policing, and inattention to psychosocial needs. We argue that the maintenance of knowledge and power networks are fundamental aspects of reality maintenance in intensive care. The social reproduction of typifi cations among nurses about consumers positioned these patients as disrupting the proper business of intensive care units; a process that we argue is bound up with the imbalanced power relationships. Further, intensive care staff maintain power structures serving intensive care interests, such as physiological rescue and the preservation of biomedical authority. We conclude that the production and reproduction of intensive care nursing knowledge maintains a social-power structure at odds with the needs of consumers.

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)0.005
metaresearch head score (Gemma)0.006
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0090.073
Scholarly communication0.0080.006
Open science0.0010.011
Research integrity0.0020.003
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 head0.130
GPT teacher head0.387
Teacher spread0.257 · 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
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
Published2020
Admission routes1
Has abstractyes

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