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Record W153242814

Framing action: assessing the impact of obesity framing on program design in British Columbia

2009· dissertation· en· W153242814 on OpenAlexfundaboutno aff
Lindsay Anne Zibrik

Bibliographic record

VenueSummit (Simon Fraser University) · 2009
Typedissertation
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsnot available
FundersHealth Canada
KeywordsFraming (construction)Media studiesPolitical scienceSociologyEngineeringCivil engineering
DOInot available

Abstract

fetched live from OpenAlex

The percentage of Canadians who are overweight or obese has risen dramatically in the past twenty years, prompting federal and provincial governments to take action on obesity. This thesis studies the impact of obesity framing on program design in BC. The focus of this thesis is two-fold. First, it is demonstrated how ideas and discursive processes are framing obesity as a health individualism construct. Second, it is shown how dominant obesity orthodoxy is impacting the design and creation of obesity intervention strategies in BC. It is shown that antiobesity literature has been instrumental in framing obesity as a serious health problem for which individuals are ultimately responsible. Moreover, it is argued that obesity program design in BC has centered on obesity as a health individualism construct, which has had the effect of relegating Government to a resource-base, relying on nodality-based policy instruments such as self-serve e-health resources and information campaigns.

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)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.648

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.045
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0090.004
Scholarly communication0.0040.001
Open science0.0020.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.056
GPT teacher head0.402
Teacher spread0.346 · 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 designObservational
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
Published2009
Admission routes2
Has abstractyes

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