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Record W2039374209 · doi:10.1097/nmd.0b013e3181b3af0c

Perception That “Everything Requires a Lot of Effort”

2009· article· en· W2039374209 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.

Bibliographic record

VenueThe Journal of Nervous and Mental Disease · 2009
Typearticle
Languageen
FieldPsychology
TopicSocial Representations and Identity
Canadian institutionsMcGill UniversityUniversité du Québec à MontréalUniversity of Ottawa
Fundersnot available
KeywordsPerceptionPsychologyComputer scienceNeuroscience

Abstract

fetched live from OpenAlex

This brief report illustrates how the migration context can affect specific item validity of mental health measures. The SCL-25 was administered to 432 recently settled immigrants (220 Haitian and 212 Arabs). We performed descriptive analyses, as well as Infit and Outfit statistics analyses using WINSTEPS Rasch Measurement Software based on Item Response Theory. The participants' comments about the item You feel everything requires a lot of effort in the SCL-25 were also qualitatively analyzed. Results revealed that the item You feel everything requires a lot of effort is an outlier and does not adjust in an expected and valid fashion with its cluster items, as it is over-endorsed by Haitian and Arab healthy participants. Our study thus shows that, in transcultural mental health research, the cultural and migratory contexts may interact and significantly influence the meaning of some symptom items and consequently, the validity of symptom scales.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.632
Threshold uncertainty score0.206

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)0.0000.000

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 head0.029
GPT teacher head0.347
Teacher spread0.317 · 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