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Métis older adults and the negotiation of nativeness

2021· book-chapter· en· W3150161219 on OpenAlexaboutno aff
John Lewis

Bibliographic record

VenuePolicy Press eBooks · 2021
Typebook-chapter
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOutreachNegotiationBaby boomersGovernment (linguistics)Political sciencePopulationEconomic growthPublic administrationBusinessSociologyEconomicsDemographyDemographic economics

Abstract

fetched live from OpenAlex

This chapter refers to community planners and local government decision makers that are acutely aware of the changing demographic character of North American communities. It examines the retirement of the baby boomer generation, which is projected that 20 percent of the North American population will be 65 years or older. It also recounts how the Age-Friendly Communities (AFC) movement acquired considerable policy and research traction since its launch by the World Health Organization (WHO) in 2007. The chapter discusses that the province of Ontario has made several incremental efforts to expand its AFC policy efforts based on three linked strategic policies and investments. It includes the launch of the <italic>Finding the Right Fit Age-Friendly Communities Planning Guide</italic> , the Ontario AFC Planning Grants Program, and funding for an AFC Outreach and Community Support Program.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.887
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.290
Teacher spread0.267 · 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 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
Published2021
Admission routes1
Has abstractyes

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