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Record W2587458424

Adult Learning for Active Citizenship: Exploring Learning Pathways around Citizenship and Participation in Community Organizations and Governance

2009· article· en· W2587458424 on OpenAlexaboutno aff
Patricia Gouthro

Bibliographic record

VenueNew Prairie Press (Kansas State University) · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicAdult and Continuing Education Topics
Canadian institutionsnot available
Fundersnot available
KeywordsActive citizenshipCitizenshipLifelong learningCorporate governanceGovernment (linguistics)Political sciencePublic relationsNeoliberalism (international relations)SociologyInformal learningAdult educationPedagogySocial scienceManagementPolitics
DOInot available

Abstract

fetched live from OpenAlex

Understanding what motivates adult to engage in various learning endeavours across the lifespan often involves tracing multiple complicated and interconnected factors. Both formal and informal educational contexts determine how individuals will be politically involved through different stages in their lives. In a current study on lifelong learning, citizenship, and participation in community-based organizations in Canada, the possibilities and challenges of developing a more networked approach towards governance to support an active and engaged citizenry is explored. This study is funded by the Canadian Council on Learning (CCL) and builds on previously completed research around women’s lifelong learning trajectories in adult and higher education in Canada funded by the Social Science and Humanities Research Council of Canada, as well as a previous CCL study on life histories of women as active citizens. The findings reveal a complex meshwork of factors that shape decisions around participation in both formal and informal learning contexts to become “active citizens”. Differing perspectives are explored around the role of government, community-based organizations (CBO’s), and volunteer participation as these relate to governance. Critical discourses in citizenship are used to explore how localized factors are often influenced by the effects of globalization and neoliberalism.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.428
Threshold uncertainty score0.787

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.047
GPT teacher head0.281
Teacher spread0.234 · 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

Citations1
Published2009
Admission routes1
Has abstractyes

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