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Record W2546397098 · doi:10.1177/0008417416668859

Partnership in research

2016· article· en· W2546397098 on OpenAlexvenueno aff
Isabelle Gélinas

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2016
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipContext (archaeology)Public relationsKey (lock)Medical educationEngineering ethicsPsychologyKnowledge managementPolitical scienceMedicineEngineeringComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Partnerships in occupational therapy between practitioners and researchers are important to advance knowledge relevant to clinical practice and support evidence-based practice in the profession. PURPOSE: This Muriel Driver lecture discusses why we should support practitioners' engagement in research and examines essential conditions required for successful collaborative partnerships in research. KEY ISSUES: Collaborative partnerships can alleviate the challenges preventing practitioners from participating in research and ensure that research initiatives are more relevant to clinical practice. Key factors for building and sustaining meaningful partnerships include the presence of favourable pre-partnership conditions related to the context and the use of guiding principles focusing on vision, values, trust, communication, power sharing, and interactions. IMPLICATIONS: Several of the factors found to foster a good collaborative partnership are consistent with our core competency roles and reflect our professional values. Being mindful of these factors when initiating research collaborations would increase the likelihood of success.

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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.786
GPT teacher head0.644
Teacher spread0.142 · 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

Citations14
Published2016
Admission routes1
Has abstractyes

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