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Record W2145743205 · doi:10.1177/1049732307308514

From Interdisciplinary to Transdisciplinary Research: A Case Study

2008· article· en· W2145743205 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.

Bibliographic record

VenueQualitative Health Research · 2008
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsUniversity of AlbertaAthabasca UniversityAlberta Health Services
Fundersnot available
KeywordsMultidisciplinary approachBioethicsEngineering ethicsTransdisciplinarityResearch ethicsSociologyManagement scienceSocial sciencePolitical scienceEngineering

Abstract

fetched live from OpenAlex

The specialization of contemporary academia necessitates the adoption of a multidisciplinary approach to study topics that cross multiple disciplines, including the area of medical ethics. However, the nature of multidisciplinary research is limited in some regards, further requiring some researchers to use interdisciplinary and transdisciplinary approaches. The authors present as a case study a research project in bioethics that began as an interdisciplinary study and which, through the research process, moved to being a transdisciplinary study in health ethics. They outline not only this transformation but also the strengths and difficulties of transdisciplinary research in the area of ethics.

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
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativemedium
gptMetaresearch
Domain: Methods · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativemedium
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)0.229
metaresearch head score (Gemma)0.046
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.183
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2290.046
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0240.002
Scholarly communication0.0000.000
Open science0.0010.003
Research integrity0.0000.029
Insufficient payload (model declined to judge)0.0020.007

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 head0.917
GPT teacher head0.813
Teacher spread0.104 · 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