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Record W2773514043

Charting the Progression of Diabetes Mellitus in New Brunswick: Rates, Correlates, and Implications for Accountability in Public Policy

2017· article· en· W2773514043 on OpenAlexaffabout
Neeru Gupta

Bibliographic record

VenueJournal of New Brunswick Studies / Revue d’études sur le Nouveau-Brunswick · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsAccountabilityDiabetes mellitusPovertySocioeconomic statusPublic healthGovernment (linguistics)MedicineEnvironmental healthPopulationGerontologyPolitical scienceEconomic growthEconomics
DOInot available

Abstract

fetched live from OpenAlex

Diabetes mellitus is one of the most common chronic conditions in New Brunswick, associated with a myriad of health and social consequences. The recent provincial government diabetes strategy focused largely on clinical indicators of diabetes prevention and management, without identification of a validated methodology for their measurement against performance targets or accountability for tangible improvements in the underlying social factors known to fuel type 2 diabetes. This study uses different data sources and methods to transparently measure recent trends in diabetes prevalence; disentangle the independent effects of multiple health, behavioural, and socioeconomic contributing factors to diabetes; and project future numbers. Population aging means the prevailing trend of rising diabetes prevalence is likely to continue in New Brunswick, but meaningful actions to address underlying social issues including poverty as a barrier to healthy living could help stem the tide.

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)0.009
metaresearch head score (Gemma)0.038
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 score0.090
Threshold uncertainty score0.212

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.038
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.011
Science and technology studies0.0010.002
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0000.002
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 head0.083
GPT teacher head0.356
Teacher spread0.273 · 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

Citations4
Published2017
Admission routes2
Has abstractyes

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