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Record W2886232785 · doi:10.1787/5k9fmrlbh942-en

Building Flexibility and Accountability into Local Employment Services

2010· paratext· en· W2886232785 on OpenAlexfundaboutno aff
Donna E. Wood

Bibliographic record

VenueOECD local economic and employment development (LEED) working papers · 2010
Typeparatext
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsnot available
FundersHuman Resources and Skills Development CanadaGovernment of Canada
KeywordsAccountabilityFlexibility (engineering)UnemploymentContext (archaeology)Labour market flexibilityBusinessEconomicsEconomic growthPublic administrationPolitical scienceManagementGeography

Abstract

fetched live from OpenAlex

Human resources and skills are becoming increasingly important to economic development. In the context of the economic downturn, challenges such as high youth unemployment call for a collaborative approach between local employment officials, educational institutions and wider social and economic partners. But do local labour market offices have sufficient flexibility in the implementation of their policies and programmes to contribute effectively to local strategies? If local labour market offices are to be given more flexibility, how can this be reconciled with the need for accountability and the achievement of national policy goals?The Canada case study for the Building Flexibility and Accountability into Local Employment Services project explores the level of local accountability and flexibility within labour market policy in Canada, focusing in particular on the provinces of Alberta and New Brunswick. This report is one of four country reports, with the other participating countries being Belgium, Denmark and the Netherlands.

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)0.031
metaresearch head score (Gemma)0.044
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.096
Threshold uncertainty score0.252

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.044
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0120.013
Scholarly communication0.0150.011
Open science0.0030.028
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0140.002

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 head0.040
GPT teacher head0.334
Teacher spread0.294 · 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 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

Citations3
Published2010
Admission routes2
Has abstractyes

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Same venueOECD local economic and employment development (LEED) working papersSame topicHealthcare innovation and challengesFrench-language works237,207