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Record W2127878365 · doi:10.3152/030234209x460980

Multiple institutional rationalities in the regulation of health technologies: an ethnographic examination

2009· article· en· W2127878365 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueScience and Public Policy · 2009
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsDalhousie University
Fundersnot available
KeywordsTransformative learningDisciplineRationalityEthnographyProcess (computing)Cross disciplinarySociologyPublic relationsPolitical scienceSocial scienceLawComputer science

Abstract

fetched live from OpenAlex

The regulation of risk associated with health technologies uses scientific evaluation to identify harms and protect citizens. However, in some cases scientific uncertainty has resulted in regulatory failures (e.g. Cox-2 inhibitors) and led regulators to explore new ways of working, such as bringing in the expertise of new actors (patient groups, community health workers, caregivers, etc.), to provide evidence and assessment in the regulation of risk. Implementing changes, however, can be an uncertain process in itself. Regulatory institutions are populated with actors representing a range of disciplinary perspectives, priorities, and values, which all influence their rationality towards accepting an introduced innovation. This paper provides an ethnographic exploration of disciplinary boundaries and multiple rationalities during a period of institutional transformation, within the Canadian Health Products and Food Branch. We interpret our findings through a multiple rationalities framework, illuminating the processes and practices of transformative risk regulation.

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.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.891
Threshold uncertainty score0.583

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.497
GPT teacher head0.563
Teacher spread0.065 · 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