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Record W2006844660 · doi:10.1177/000841740106800506

Expanding the Boundaries of Occupational Therapy Practice through Student Fieldwork Experiences: Description of a Provincially-Funded Community Development Project

2001· article· en· W2006844660 on OpenAlexafffundvenueabout
Judith Friedland, Helene J. Polatajko, Marie Gage

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2001
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsUniversity of Toronto
FundersCouncil of Ontario Universities
KeywordsOccupational therapyWork (physics)Christian ministryGovernment (linguistics)Promotion (chess)Medical educationRehabilitationService (business)NursingMedicinePublic relationsPsychologyPolitical scienceBusinessEngineeringPolitics

Abstract

fetched live from OpenAlex

The numbers of occupational therapists in community practice are not yet large enough to provide fieldwork placements to accommodate all students. This article describes a project designed to educate community agencies that do not employ occupational therapists, about our service while at the same time securing new fieldwork placements. We used on-site different discipline and offsite same discipline supervision to provide students to selected agencies without cost. Funding for one year from the Ontario Ministry of Health to the Ontario University Programs in Rehabilitation Science enabled us to initiate and evaluate the project. Students in the project developed their ability to work independently and to see their potential role in health promotion and prevention. Despite the lack of ongoing government funding, four years later, community sites are not only being maintained, but the number of sites has increased from 28 to 39, providing a total of 75 student placements. By educating a growing number of community agencies about the work of occupational therapists, the project has also expanded the boundaries of practice.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.253
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.519
GPT teacher head0.552
Teacher spread0.033 · 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 designObservational
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

Citations38
Published2001
Admission routes4
Has abstractyes

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