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Record W2531859717 · doi:10.1016/j.ypmed.2016.10.002

The impact of changes in social policies on household food insecurity in British Columbia, 2005–2012

2016· article· en· W2531859717 on OpenAlexafffundabout
Na Li, Naomi Dachner, Valerie Tarasuk

Bibliographic record

VenuePreventive Medicine · 2016
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health ResearchHealth Canada
KeywordsFood insecurityPsychological interventionFood securityEnvironmental healthGovernment (linguistics)MedicineFood pricesSocioeconomicsEconomic growthGeographyEconomicsAgriculture

Abstract

fetched live from OpenAlex

As concerns about food insecurity in high income countries grow, there is a need to better understand the impact of social policy decisions on this problem. In Canada, provincial government actions are particularly important because food insecurity places substantial burden on provincial health care budgets. This study was undertaken to describe the socio-demographic and temporal patterning of food insecurity in British Columbia (BC) from 2005 to 2012 and determine the impact of BC's one-time increase in social assistance and introduction of the Rental Assistance Program (RAP) on food insecurity rates among target groups. Using data from the Canadian Community Health Surveys, logistic regression analyses were conducted to identify trends and assess changes in food insecurity among subgroups differentiated by main source of income and housing tenure. Models were run against overall food insecurity, moderate and severe food insecurity, and severe food insecurity to explore whether the impact of policy changes differed by severity of food insecurity. Overall food insecurity rose significantly among households in BC between 2005 and 2012. Following the increase in social assistance benefits, overall food insecurity and moderate and severe food insecurity declined among households on social assistance, but severe food insecurity remained unchanged. We could discern no effect of the RAP on any measure of food insecurity among renter households. Our findings indicate the sensitivity of food insecurity among social assistance recipients to improvements in income and highlight the importance of examining severity of food insecurity when assessing the effects of policy interventions.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.747
Threshold uncertainty score0.895

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.193
GPT teacher head0.453
Teacher spread0.260 · 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.

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

Citations70
Published2016
Admission routes3
Has abstractyes

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