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Post-Adult Education Alternatives in 45 Years of Learning/Teaching

2018· book-chapter· en· W2902168749 on OpenAlexaffabout
R. M. Fisher

Bibliographic record

VenueAdvances in educational technologies and instructional design book series · 2018
Typebook-chapter
Languageen
FieldSocial Sciences
TopicAdult and Continuing Education Topics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsIdeologyMainstreamNeoliberalism (international relations)ContextualizationSociologySociocultural evolutionNegotiationPedagogyPoliticsPolitical scienceSocial science

Abstract

fetched live from OpenAlex

The author critically examines the directional trends that education has gone through in the last 45 years of his teaching and learning experiences, primarily in Alberta, Canada (1972-2017). He argues that, formerly, Alberta was at the leading edge of positive progressive change, before neoliberal ideology invaded Education. Through use of autoethnographic reflection and sociocultural and political contextualization of his educational experiences, the author elaborates the necessity of adopting a holistic-integral alternative path to research and teaching outside of institutionalized mainstream education systems. His emphasis on the affective domain, for example the importance of fear in education, is accompanied by his applications of developmental notions of “post-adult,” transdisciplinary, and integral theoretical work. The purpose of the chapter is to demonstrate, through his own life, a model of potential guidance for teachers, who are questioning how best to negotiate their own careers within the challenges of 21st century neoliberalism and cascading global crises.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.178
Threshold uncertainty score0.354

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.005
Scholarly communication0.0050.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.010
GPT teacher head0.293
Teacher spread0.283 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2018
Admission routes2
Has abstractyes

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