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Record W2047365670 · doi:10.1080/14427591.2008.9686623

A vision for occupational science: Reflecting on our disciplinary culture

2008· article· en· W2047365670 on OpenAlexaff
Debbie Laliberté Rudman, Silke Dennhardt, Daniel Fok, Suzanne Huot, Daniel Molke, Anna Park, Briana Zur

Bibliographic record

VenueJournal of Occupational Science · 2008
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsWestern University
Fundersnot available
KeywordsOccupational scienceDisciplineReflexivitySociologyEpistemologyPluralism (philosophy)Engineering ethicsContext (archaeology)Relevance (law)Identity (music)Occupational therapySocial sciencePsychologyPolitical scienceAestheticsEngineering

Abstract

fetched live from OpenAlex

This paper highlights and discusses key questions for the continued development of occupational science, contending that reflexivity and dialogue addressing these questions are essential to achieve complex understandings of occupation. The questions, which relate to disciplinary identity, the relation between science and practice, relevance, interdisciplinarity and internationalization, evolved from dialogue amongst the authors who collectively worked towards a shared vision for occupational science in the context of a doctoral course. This paper does not seek to build consensus around this vision, but rather identifies issues vital to consider as occupational science continues to evolve. Disciplinary culture is proposed to be a useful starting point for dialogue, as this encompasses the values, assumptions and beliefs that shape what we seek to know about occupation and how we seek to know. The paper also calls for further consideration of pluralism in relation to occupational science.

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)0.090
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.955
Threshold uncertainty score0.474

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0900.047
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.003
Science and technology studies0.0450.154
Scholarly communication0.0500.038
Open science0.0040.040
Research integrity0.0100.029
Insufficient payload (model declined to judge)0.0020.001

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 head0.449
GPT teacher head0.665
Teacher spread0.216 · 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.

Study designTheoretical or conceptual
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

Citations65
Published2008
Admission routes1
Has abstractyes

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