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Record W576370337 · doi:10.4324/9781351312004

Employability : from theory to practice

2001· book· en· W576370337 on OpenAlexaboutno aff
Patricia Weinert

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicHigher Education Learning Practices
Canadian institutionsnot available
Fundersnot available
KeywordsEmployabilityWorkforceUnemploymentLabour economicsSeekersPublic relationsPolitical scienceBusinessEconomicsEconomic growthLaw

Abstract

fetched live from OpenAlex

In the struggle against unemployment and marginalization, employability has become the one major tool to counteract this phenomenon. Those who have no chances to develop or enhance their employability will fail in the competitive labor market of the new economic order. While the notion of employability is not exactly new, the weight now being placed upon it is new: to equip job seekers for the far-reaching changes currently taking place in the economy and the world of work. What is at stake? Is employability an instrument for the regulation of the labor market, distinguishing between the employable and the unemployable? Or is it a set of measures to facilitate the insertion or reinsertion of workers into the workforce? Is employability in the future the defining policy framework for labor market policies? What are the consequences of such a development for policy makers? Employability: From Theory to Practice addresses these questions. Its internationally renowned authors provide a valuable contribution to the conceptual and operational content of the notion of employability. The form and content of measures of employability vary by state, but represent a general trend. Part 1 deals with the concepts and instruments of employability. Part 2 evaluates measures implemented in a number of countries to improve employability of job-seekers. The countries involved are the UK, the Netherlands, Belgium, Ireland, New Zealand, Poland, and Slovakia. Part 3 showcases a practical approach with Canada, which in 1996-97 moved from an unemployment to an employment insurance. This volume shows both the possibilities and limitations of measures to promote employability. It helps clarify complex policy questions which will contribute to a better understanding of the concept for policy makers and administrators. It will help policy makers, professionals, and scholars assess current trends in the workplace.

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)0.024
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.036
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.005
Science and technology studies0.0040.060
Scholarly communication0.0130.018
Open science0.0040.010
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0060.002

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 head0.032
GPT teacher head0.413
Teacher spread0.381 · 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 designTheoretical or conceptual
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

Citations35
Published2001
Admission routes1
Has abstractyes

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