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Congruency in Higher Learning

2011· book-chapter· en· W2787082876 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.863
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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