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Record W2129212733 · doi:10.1177/0950017005051298

‘I’m still scrubbing the floors’

2005· article· en· W2129212733 on OpenAlexafffundabout
Wolfgang Lehmann

Bibliographic record

VenueWork Employment and Society · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Education and Societal Dynamics
Canadian institutionsWestern University
FundersUniversity of Alberta
KeywordsApprenticeshipAffect (linguistics)GermanWork (physics)Public relationsSchool-to-work transitionPsychologyPedagogyPolitical scienceVocational educationEngineering

Abstract

fetched live from OpenAlex

Based on interviews with youth in Canada participating in a high school based apprenticeship programme, this article investigates the extent to which such programmes affect stated policy goals of facilitating school-work transitions and developing workplace skills. Although embedded in very different education and labour market structures, Germany’s dual system is often discussed as a successful model for youth apprenticeship programmes. A comparison between Canadian and German youth apprentices therefore provides a rare critical look at how these differences shape individual experiences in apprenticeships, but also how they affect the accomplishment of policy goals. Findings show that the study participants themselves viewed their apprenticeships as positive and meaningful experiences. Yet the Canadian apprentices had only a cursory knowledge of apprenticeship regulations and career paths, and the German apprentices were restricted in their choices by the early streaming processes in Germany’s education system. Skill development in Canada was limited by a focus on workplace-readiness skills and a lack of integration of what participants did at work and what they learned at school. Rather than gaining an understanding of their rights and responsibilities in the workplace, they were learning to accept their under-privileged place in it.

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)0.003
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.761
Threshold uncertainty score0.482

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.006
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.027
GPT teacher head0.304
Teacher spread0.277 · 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

Citations26
Published2005
Admission routes3
Has abstractyes

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