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Record W2160219625 · doi:10.1093/heapro/daq052

Moving Canadian governmental policies beyond a focus on individual lifestyle: some insights from complexity and critical theories

2010· article· en· W2160219625 on OpenAlexafffundabout
Carlos Gonçalves Neto Alvaro, Lois Jackson, Sara Kirk, Tara-Leigh McHugh, Jean Hughes, Andrea Chircop, Renée Lyons

Bibliographic record

VenueHealth Promotion International · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsUniversity of AlbertaNova Scotia Health AuthorityCapital District Health AuthorityBridgepoint Active HealthcareIzaak Walton Killam Health CentreUniversity of TorontoDalhousie University
FundersInstitute of Population and Public HealthCanadian Institutes of Health ResearchDalhousie University
KeywordsGovernment (linguistics)Context (archaeology)Psychological interventionPovertyAction (physics)Political scienceSociologyPublic relationsPsychologyGeography

Abstract

fetched live from OpenAlex

This paper explores why Canadian government policies, particularly those related to obesity, are 'stuck' at promoting individual lifestyle change. Key concepts within complexity and critical theories are considered a basis for understanding the continued emphasis on lifestyle factors in spite of strong evidence indicating that a change in the environment and conditions of poverty isare needed to tackle obesity. Opportunities to get 'unstuck' from individual-level lifestyle interventions are also suggested by critical concepts found within these two theories, although getting 'unstuck' will also require cross-sectoral collective action. Our discussion focuses on the Canadian context but will undoubtedly be relevant to other countries, where health promoters and others engage in similar struggles for fundamental government policy change.

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)0.010
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.229
Threshold uncertainty score0.895

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.007
Science and technology studies0.0280.081
Scholarly communication0.0180.008
Open science0.0030.006
Research integrity0.0040.007
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 head0.040
GPT teacher head0.331
Teacher spread0.290 · 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 designTheoretical or conceptual
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

Citations133
Published2010
Admission routes3
Has abstractyes

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