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Record W2081290576 · doi:10.1177/102425890401000205

The Danish model of ‘flexicurity’: experiences and lessons

2004· article· en· W2081290576 on OpenAlexaboutno aff
Per Kongshøj Madsen

Bibliographic record

VenueTransfer European Review of Labour and Research · 2004
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFlexicurityDanishSocial securityNoticeLegislationFlexibility (engineering)Employment protection legislationLabour economicsWelfareWelfare stateBusinessEuropean unionEconomicsMarket economyEconomic policyUnemploymentEconomic growthPolitical scienceLawPolitics

Abstract

fetched live from OpenAlex

The success of the Danish economy in recent years has led to claims that the Danish employment system constitutes a unique model. Danish legislation provides for a low level of employment protection, allowing employers to dismiss workers with short notice. As a result, the Danish employment system has a level of numerical flexibility that is comparable to that of liberal labour markets like those of Canada, Ireland, the United Kingdom and the United States. At the same time, through its social security system and active labour market programmes, Denmark resembles other Nordic welfare states in providing a tightly knit safety net for its citizens. The Danish model thus illustrates a possible trade-off between a very flexible employment relation and a social protection system, which, combined with active labour market programmes, defends individuals from the potential costs of a low level of employment security. The model thus represents a genuine alternative to the widespread view that it is desirable to develop a high level of individual employment protection at the company level.

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)0.008
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.057
Threshold uncertainty score0.131

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0100.015
Scholarly communication0.0110.007
Open science0.0010.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.205
GPT teacher head0.501
Teacher spread0.296 · 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 designQualitative
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

Citations144
Published2004
Admission routes1
Has abstractyes

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