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Record W2105252768 · doi:10.1177/1363461509342942

Cultural Formulation Guidelines

2009· letter· en· W2105252768 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueTranscultural Psychiatry · 2009
Typeletter
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsMcGill University
FundersCanadian Institutes of Health Research
KeywordsConstruct (python library)Process (computing)Cultural diversityCultural analysisPsychologyEngineering ethicsSociologyEpistemologyComputer scienceSocial scienceEngineeringAnthropology

Abstract

fetched live from OpenAlex

The outline for the Cultural Formulation (CF) introduced in DSM-IV does not present any method for collecting the required cultural information. The absence of specific guidelines and illustrative cases has hampered its wider use. This article offers a practical approach to preparing a Cultural Formulation as a component of culturally competent clinical care. We summarize the rationale for the four sections of the CF, describe the process of conducting culturally focused clinical interviews, and present examples of questions or lines of inquiry that can be used to collect the information needed to construct the CF. An online supplement provides case examples of cultural formulations applied to patients seen in the US.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.051
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.097
GPT teacher head0.408
Teacher spread0.311 · 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