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Record W2903329148 · doi:10.1177/0741713618815656

Taking Time to Learn: The Importance of Theory for Adult Education

2018· article· en· W2903329148 on OpenAlexaff
Patricia A. Gouthro

Bibliographic record

VenueAdult Education Quarterly · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicAdult and Continuing Education Topics
Canadian institutionsMount Saint Vincent University
Fundersnot available
KeywordsAdult educationPerspective (graphical)InjusticePedagogySociologyPower (physics)Education theoryCritical theorySocial justiceArgument (complex analysis)Learning theoryProcess (computing)Action (physics)Social theoryPsychologyEpistemologyHigher educationSocial psychologySocial sciencePolitical science

Abstract

fetched live from OpenAlex

This article explores the importance of sustaining a rich and vibrant discourse of theory to inform the practice of adult education. Beginning with a brief overview of factors that have shaped the development of theory in adult education, the article then explores reasons why educators may not spend as much time teaching and learning about theory as they have in the past. For educators working from a social justice perspective, theory provides an important analytical lens to counter injustice and shape social action. Using a critical feminist perspective, the argument is made that ensuring that adult education is a practice informed by theory enables educators to understand the complexity of the teaching and learning process, encourages students to explore the ways in which power shapes our personal and social learning contexts, and fosters the development of a more critically literate and engaged citizenry.

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)0.025
metaresearch head score (Gemma)0.019
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 score0.025
Threshold uncertainty score0.130

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0070.070
Scholarly communication0.0190.021
Open science0.0030.007
Research integrity0.0040.011
Insufficient payload (model declined to judge)0.0040.001

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 head0.009
GPT teacher head0.327
Teacher spread0.318 · 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

Citations42
Published2018
Admission routes1
Has abstractyes

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