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Record W4399074444 · doi:10.4324/9781003525288-99

Canadian Occupational Performance Measure (COPM)

2024· book-chapter· en· W4399074444 on OpenAlexaboutno aff
Kevin Bortnick

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsnot available
Fundersnot available
KeywordsMeasure (data warehouse)PsychologyPhysical medicine and rehabilitationMedicineComputer scienceData mining

Abstract

fetched live from OpenAlex

The Canadian Occupational Performance Measure (COPM) is a standardized assessment that is delivered through a semi-structured interview as well as a questionnaire/rating scale designed to assess a client’s self-perception of occupational performance and satisfaction with that performance over time. It is based on the Canadian Model of Occupational Performance and is intended to help clients identify, prioritize, and evaluate important issues they encounter in occupational performance ( Law et al., 2011 ). Through discussion, the client first identifies occupational performance issues that he or she would like to work on and then ranks each item (1 to 10) relative to their importance to the individual for the following general categories: Self-care, which includes the following: Personal care Functional mobility Community management Productivity, which is composed of the following: Paid/unpaid work Household management Play/school Leisure, which is further delineated into the following subcategories: Quiet recreation Active recreation Socialization.

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)0.002
metaresearch head score (Gemma)0.005
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: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.946
Threshold uncertainty score0.259

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.008
Science and technology studies0.0030.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0670.027

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 head0.127
GPT teacher head0.443
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

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
GenreMethods

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

Citations170
Published2024
Admission routes1
Has abstractno

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