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Hidden knowledge: Working-class capacity in the ‘knowledge-based economy’

2005· article· en· W2344235358 on OpenAlexaboutno aff
D. W. Livingstone, Peter H. Sawchuk

Bibliographic record

VenueStudies in the Education of Adults · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsWorking classContext (archaeology)Class (philosophy)Adult educationKnowledge economySociologyPolitical sciencePublic relationsPedagogyLawArtificial intelligencePoliticsComputer science

Abstract

fetched live from OpenAlex

The research reported in this paper attempts to document the actual learning practices of working-class people in the context of the much heralded ‘knowledge-based economy’. Our primary thesis is that working-class peoples' indigenous learning capacities have been denied, suppressed, degraded or diverted within most capitalist schooling, adult education institutions and employer-sponsored training programmes, at the same time as working class informal learning and tacit knowledge are heavily relied on to actually run paid workplaces. Our analysis is based on five case studies of Canadian union locals which document the learning practices of hired workers based in different industries and employment sites with strikingly different support systems for education and training and working-class learning generally. We criticise dominant theories of adult education for preoccupation with a historical and individualised, psychological processes and motives while ignoring the collective learning processes that working-class people rely upon most. For this reason we rely on a cultural-historical theory of adult learning. These case studies show that workers are generally active learners, that they do much of their learning informally and that much of this learning is of high quality.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.425
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.404
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 teacher head, 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

Citations25
Published2005
Admission routes1
Has abstractyes

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