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Record W2214701484 · doi:10.1787/5jrnwqk5d4f7-en

Local economic strategies for ageing labour markets

2015· report· en· W2214701484 on OpenAlexaboutno aff
Peter Hicks

Bibliographic record

VenueOECD local economic and employment development (LEED) working papers · 2015
Typereport
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Face (sociological concept)Local communityLocal economic developmentPolitical scienceEconomic growthBusinessSociologyEconomicsGeographySocial scienceLawArchaeology

Abstract

fetched live from OpenAlex

This working paper examines the impacts of the Canadian employment strategy, the Targeted Initiative for Older Workers, in the Fort St. James community in north-central British Columbia. The paper notes that older workers are generally well employed at the aggregate level in Canada, but may face specific challenges in local and vulnerable communities. An examination of the design of this project highlights the need for clear objectives, eligibility criteria, local sponsors and group-based support. In the context of the Fort St. James Community, participants and administrators highlighted the efficacy of custom and individual support in creating better outcomes for older workers.

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)0.002
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.377
Threshold uncertainty score0.750

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0080.004
Scholarly communication0.0080.002
Open science0.0010.008
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0250.002

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 head0.043
GPT teacher head0.295
Teacher spread0.252 · 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
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

Citations1
Published2015
Admission routes1
Has abstractyes

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