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Record W1810094406 · doi:10.1596/17045

Governance of Multi-sectoral Interventions to Promote Healthy Living in Latin America and the Caribbean

2013· book· en· W1810094406 on OpenAlexaboutno aff
María Eugenia Bonilla-Chacín

Bibliographic record

VenueWorld Bank, Washington, DC eBooks · 2013
Typebook
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsLatin AmericansGovernment (linguistics)Public healthCorporate governancePopulationHealth promotionPsychological interventionEconomic growthPolitical scienceEpidemiological transitionCaribbean regionBusinessEnvironmental healthPopulation healthMedicineDevelopment economicsEconomicsFinance

Abstract

fetched live from OpenAlex

The Latin America and Caribbean (LAC) region has been experiencing a rapid demographic and epidemiological transition which has important health and economic consequences. Not only is the population aging rapidly, but it is also experiencing major changes in lifestyle. This has altered the disease and mortality profile, reflected in the increasing weight of Non-Communicable Diseases (NCDs), such as heart disease, stroke, cancer and diabetes. These conditions also represent an increasing economic and development threat to households, health systems, and economies. The study also ranked tobacco use among the first five risk factors in LAC and alcohol abuse as the main risk factor in all sub-regions, with the exception of the Caribbean and southern LAC, where alcohol was ranked among the first five. However, voluntary actions are often ineffective and policymakers have replaced them with regulations. For example, in Europe, Canada, and the US, early voluntary nutrition labeling actions failed to meet government standards and expectations which led governments to use mandatory guidelines. In New York City, authorities encouraged restaurants to voluntarily provide easily-seen nutrition information to customers, but, as this did not occur, the City passed a regulation. In general, policymakers and health advocates often gauge and mobilize public opinion to support these health promotion policies and ensure their design and implementation.

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.274
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.038
GPT teacher head0.294
Teacher spread0.256 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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
Published2013
Admission routes1
Has abstractyes

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