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Congruency in Higher Learning

2011· book-chapter· en· W2787082876 on OpenAlexaff
Karim A. Remtulla

Bibliographic record

VenueIGI Global eBooks · 2011
Typebook-chapter
Languageen
FieldSocial Sciences
TopicHigher Education Learning Practices
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAdult educationCongruence (geometry)Higher educationAdult LearningCore (optical fiber)SustainabilityPsychologyPedagogyIdeal (ethics)Public relationsPolitical scienceSociologySocial psychologyEngineering

Abstract

fetched live from OpenAlex

The core elements of people, processes, technology, and stakeholders remain similar for most higher learning institutions today. Yet, to culturally promote any one particular ‘form’ of adult education as ‘ideal’ for ‘all’ adult learners is increasingly exclusionary. The objective of this chapter is to enable future educational instructors, administrators, and leaders to respond to the changing needs of adult learners regarding congruence between core elements of higher learning institutions and sustainability of adult education program policies. Emanating from the seminal thinking of Carl R. Rogers, the opening sections of this chapter address personal and peripheral congruence. Then, the main section of this chapter puts forward a congruency-based framework for sustainable adult education program policies in higher learning institutions. Developing ‘congruent form(s)’ using core organizational elements will likely result in more socially just and culturally inclusive adult education and higher learning for diverse and global learner cohorts in the digital age.

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)0.003
metaresearch head score (Gemma)0.003
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: Other · Consensus signal: Other
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.021
Scholarly communication0.0090.006
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.067
GPT teacher head0.340
Teacher spread0.273 · 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
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

Citations3
Published2011
Admission routes1
Has abstractyes

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