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Record W1980348059 · doi:10.1177/000841740807500513

Qualitative Meta-Synthesis: Reflections on the Utility and Challenges in Occupational Therapy

2008· article· en· W1980348059 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2008
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsMcMaster UniversityToronto Rehabilitation InstituteUniversity of Toronto
Fundersnot available
KeywordsQualitative researchPhenomenonInterpretation (philosophy)Computer scienceManagement scienceEngineering ethicsKnowledge managementEpistemologyPsychologySociologyEngineeringSocial science

Abstract

fetched live from OpenAlex

BACKGROUND: A qualitative meta-synthesis is an approach to synthesizing relevant findings from across qualitative studies on a particular topic using methods consistent with qualitative research. PURPOSE: Using examples of recently completed qualitative meta-synthesis projects, the purpose of this paper is to present the meta-synthesis approach; highlight the key steps, processes, and issues involved; and demonstrate its potential to advance knowledge about occupation and occupation-based practice. KEY ISSUES: The qualitative meta-synthesis approach allows us to take stock of the current state of knowledge in a given area in order to ensure that we have explored the phenomenon from different perspectives and to begin to push the field forward by allowing us to develop deeper insights and understandings. IMPLICATIONS: Despite certain limitations and challenges associated with the approach, qualitative meta-syntheses can provide new knowledge through critical analysis and interpretation to inform client, practitioner, and policy audiences.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gptMeta-epidemiology (broad)
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
grokMetaresearch
Domain: Methods · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptualhigh
opusMetaresearch
Domain: Methods · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptualmedium
models splitAgreement compares identical category sets and study designs across arms.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient 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 score0.467
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.901
GPT teacher head0.619
Teacher spread0.282 · 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