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Record W2105184148 · doi:10.18740/s4mk56

Labour Market Policies in Denmark and Canada: Could Flexicurity be an Answer for Canadian Workers?

2012· article· en· W2105184148 on OpenAlexaffvenueabout
Leslie Nichols

Bibliographic record

VenueSocialist studies · 2012
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsFlexicurityNexus (standard)Labour economicsWork (physics)WelfareSocial securityGovernment (linguistics)DisadvantageEmployabilityUnemploymentActive labour market policiesOrder (exchange)Social policySocial insuranceEconomicsPrecarious workBusinessPolitical scienceEconomic growthMarket economyLawFinance

Abstract

fetched live from OpenAlex

Abstract The labour market in Canada is changing. Over the past decades there has been an increase in the number of precarious workers on short-term, part-time, contracts; jobs are created and lost, as employers deem necessary. As a result of these shifts in the organization of work, many workers are now forced to hold multiple jobs in order to make ends meet. This move away from long-term employment has created a situation where the majority of Canadian workers can no longer expect their employer to provide predictable support and security for them. At the same time, under the current Employment Insurance (EI) laws, they cannot expect support from the federal government either. How can workers gain some immediate protection through expanded social welfare programmes? With more and more workers, especially women, racialized workers and lower income people relegated to precarious employment, we must question current social policy. If, as it appears, EI does not work, we must strive to implement a viable alternative. Could an alternative system be modeled on the flexicurity system now in effect in Denmark? This paper draws on Nancy Fraser’s criteria for social justice for the globalized worker, to assess the ways that flexicurity could improve the security of the Canadian worker by offering alternatives to participation in the market nexus.

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)0.003
metaresearch head score (Gemma)0.007
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: Empirical · Consensus signal: none
Teacher disagreement score0.182
Threshold uncertainty score0.949

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0150.004
Scholarly communication0.0070.002
Open science0.0020.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0080.000

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 head0.110
GPT teacher head0.442
Teacher spread0.332 · 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
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
Published2012
Admission routes3
Has abstractyes

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