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Record W4244147197 · doi:10.1002/9780470515167.ch4

The Cultural Context of Clinical Assessment

2008· other· en· W4244147197 on OpenAlexaff
Laurence J. Kirmayer, Cécile Rousseau, G. Eric Jarvis, Jaswant Guzder

Bibliographic record

Venuenot available
Typeother
Languageen
FieldPsychology
TopicCounseling Practices and Supervision
Canadian institutionsMcGill University
Fundersnot available
KeywordsMainstreamPsychologyCultural competenceNegotiationEthnic groupCultural diversityPopulationMental healthSocial psychologyPsychotherapistMedicineSociologyPolitical sciencePedagogySocial science

Abstract

fetched live from OpenAlex

Careful evaluation of the cultural context of psychiatric problems must form a central part of any clinical assessment. The outline for a cultural formulation in DSM-IV-TR provides a useful checklist of basic issues to address, including the cultural, ethnic, religious, and linguistic identity of the patient; illness explanations and healing practices; social stress, support, and functioning; and models of the roles and relationship of doctor and patient. Psychiatric theory and practice reflect cultural assumptions that patients and clinicians may not share. Lack of awareness of important differences between patients and clinicians on any of these dimensions can undermine the development of a therapeutic alliance and the negotiation and delivery of effective treatment. Mainstream care cannot respond adequately to the needs of a diverse population unless it gives explicit attention to cultural issues. The ethnocultural diversity of mental health professionals itself represents an invaluable resource. The training programs must recognize this, and make it safe for clinicians to explore their own ethnocultural background and assumptions as a path to more sensitive and responsive work with others. Ultimately, cultural competence involves knowing one's own assumptions, biases, and limitations, and working collaboratively with patients, their families, and community as well as with trained interpreters and culture-brokers, toward goals that have been negotiated through open dialogues.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.202
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0200.001

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 head0.128
GPT teacher head0.498
Teacher spread0.370 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations18
Published2008
Admission routes1
Has abstractyes

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