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Record W2773476657

Population Change and Population Health: A Spatio-temporal Analysis of New Brunswick Communities

2017· article· fr· W2773476657 on OpenAlex
Paul A. Peters

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of New Brunswick Studies / Revue d’études sur le Nouveau-Brunswick · 2017
Typearticle
Languagefr
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsCarleton University
Fundersnot available
KeywordsPopulationGeographyPopulation healthContext (archaeology)Population growthHealth indicatorDemographySociology
DOInot available

Abstract

fetched live from OpenAlex

This paper considers population change in small areas of New Brunswick in relation to community-level population health indicators. Population forecasts developed via regionally constrained models are presented in conjunction with health indicators data for health zones and health council communities. Temporal and spatial variation in health indicators is discussed in relation to where population growth is forecasted to occur, and where there will be continued population decline. The results show that population growth is forecasted only for the areas surrounding Fredericton, Moncton, and Saint John, with most other areas predicted to experience continued population decline, even if the province as a whole does not. These forecasts are within a context where communities with declining population are also those with lower values across a range of non-medical determinants of health. These results present an opportunity to focus provincial strategies based on the combination of observed trends of population change and geographic inequalities of population health.

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.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.129
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0010.001
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 head0.154
GPT teacher head0.372
Teacher spread0.218 · 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