MétaCan
Menu
Back to cohort
Record W2764862479 · doi:10.1179/otb.2010.62.1.004

Learning by doing: creating knowledge for occupational therapy

2010· article· en· W2764862479 on OpenAlexaff
Mary Law

Bibliographic record

VenueWorld Federation of Occupational Therapists Bulletin · 2010
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsOccupational therapyKnowledge managementPsychologyMedicineComputer sciencePhysical therapy

Abstract

fetched live from OpenAlex

Occupational therapists open doors to occupation. The goal of occupational therapy is to enable people to engage in occupations that support and bring meaning to daily life. With this vision, we have a responsibility to create and use knowledge to ensure our commitment to the rights of all people to participate fully in daily life. Over the past 30 years, we have gained substantive knowledge from research from occupational therapy, occupational science and other disciplines. Sources of knowledge for occupational therapy come from person/people’s needs, values, dreams; therapists’ wisdom and reasoning; and research.In this paper, I examine how to use current knowledge and create the knowledge needed for the future. Specifically, I discuss dimensions of knowledge, knowledge creation frameworks, knowledge translation and the process of learning. We have a responsibility to build a knowledge creation process consistent with occupational therapy values. The creation and use of knowledge is complex and does not happen automatically. Given this complexity, we must guard against a focus on creating knowledge that applies universally and does not take into account culture, context and individual needs. Knowledge creation in occupational therapy can be a wonderful journey – bringing together experience and action to learn by doing.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.651
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.111
GPT teacher head0.482
Teacher spread0.371 · 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
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

Citations17
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueWorld Federation of Occupational Therapists BulletinSame topicOccupational Therapy Practice and ResearchFrench-language works237,207