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Record W2790037050 · doi:10.7227/jace.11.1.6

Lifelong Learning Chic in the Modern Practice of Adult Education: Historical and Contemporary Perspectives

2005· article· en· W2790037050 on OpenAlexaffabout
André P. Grace

Bibliographic record

VenueJournal of Adult and Continuing Education · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Educational Policies and Reforms
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLifelong learningAdult educationPedagogySociologyGovernment (linguistics)NeglectPerspective (graphical)Public relationsPsychologyPolitical science

Abstract

fetched live from OpenAlex

This article turns to the history of the modern practice of adult education to speak to the versatility of lifelong learning as a fluid and indeterminate concept that some have viewed as a learner's way out and others have viewed as a learner's burden. It identifies change forces that have shaped particular purposes and functions of lifelong learning over time and tides. In the wake of such forces, the article emphasises the need for a critical practice of lifelong learning that would engage citizen learner-workers in holistic practices that attend to their instrumental, social, and cultural needs. In doing so, it speaks to the importance of remembering history by using the lens of the past to consider the conceptualisation and parameters of contemporary lifelong learning and to critique a discernable culture of learner-worker neglect in Canada. Considering the plight of Canadian young adults as an example, the article provides critical reflection on federal government policy that abets privatisation of lifelong learning and aggravates the situation for learner-workers by blaming individuals for any failure in lifelong learning. It concludes with a perspective suggesting it may well be time for a critical (re)turn in Canadian adult education to help salvage lifelong learning as a formation and project of the social.

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)0.001
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 score0.302
Threshold uncertainty score0.373

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.008
GPT teacher head0.306
Teacher spread0.298 · 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

Citations7
Published2005
Admission routes2
Has abstractyes

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