MétaCan
Menu
Back to cohort
Record W7033618114

REGULATION AND GOVERNANCE OF ACCESS TO UNPROVEN MEDICAL INTERVENTIONS IN CANADA; A CASE STUDY ANALYSIS

2022· dissertation· en· W7033618114 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2022
Typedissertation
Languageen
FieldComputer Science
TopicMathematics, Computing, and Information Processing
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate governancePsychological interventionContext (archaeology)Government (linguistics)LegislatureConceptual frameworkLegislationSet (abstract data type)
DOInot available

Abstract

fetched live from OpenAlex

This research used case studies to identify and explore lessons from past regulation and governance of access to unproven medical interventions provided by physicians in Canada, with the goal of informing and strengthening future strategies. The examples selected were chelation therapy for applications other than treating heavy metal toxicity, liberation therapy for multiple sclerosis, and unproven stem cell interventions. For each case study, a systematic data collection strategy was used that included academic literature from relevant disciplines, legislation, government documents, records of legislative and parliamentary debates, jurisprudence, professional regulatory decisions and guidance, news media, and patient advocacy activity. The role of law helped set boundaries for the data collection and analysis, which focused primarily on regulatory and governance tools and strategies that use or are empowered or constrained by law. \nA second objective of this research was to develop theoretical insights regarding the use of regulation and governance as frameworks for understanding complex policy issues. Drawing on the fields of regulation and governance, a conceptual framework was developed to guide the case study analyses. This conceptual framework was revised iteratively throughout the work. The key features of regulation and governance that were identified and explored through each case study were actors, instruments, purposes, legitimacy, and responsiveness and adaptability. \nFollowing the individual case study analyses, which developed a deep understanding of each case, a cross-case analysis was conducted to identify features of the Canadian context that future regulation and governance of access to unproven medical interventions will likely need to account for to be successful. These features include our decentralized healthcare system, the importance of medical professional regulation, and our independent judicial processes. There are also several areas of focus that the findings from this research suggest may strengthen future regulation and governance of access to unproven medical interventions provided by physicians in Canada. These priorities include maximizing the potential of collaborative distributed governance, emphasizing protection of the public interest in renewal of medical professional regulation, prioritizing fairness and transparency in stakeholder engagement practices, promoting the need for clarity and nuance in discussions about evidence, and supporting strong science and health communication practices.\nThe conceptual framework developed in this work provided a systematic approach for identifying and analyzing the field of influence over the complex issues at the heart of this research and it may prove useful for future study in other fields. Bridging the fields of regulation and governance in this way also added richness and nuance to key concepts in each domain. In so doing, this research responded to calls for work that uses regulation and governance theory to inform and strengthen practice, and vice versa.

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)0.013
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.824
Threshold uncertainty score0.955

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.022
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.010
Science and technology studies0.0210.010
Scholarly communication0.0070.002
Open science0.0030.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.222
Teacher spread0.208 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueUniversity Library (University of Saskatchewan)Same topicMathematics, Computing, and Information ProcessingFrench-language works237,207