Bibliographic record
Abstract
This chapter looks at the socio-cultural implications of universalized education for workers. A universalized education for workers by workplace e-learning happens through hypermedia-centric, constructivist-based workplace e-learning that configures technologies, constructivism, and instructors, for a knowledge-based workplace. Workplace e-learning for workplace adult education and training has changed over the past decade with respect to the changes and complexities of the learning process. This is especially true given the growing prevalence of information and communication technologies (ICTs). Distance education in the tertiary sector is looked at to see what is revealed from workplace adult education and training encounters with workplace e-learning. This raises questions about workplace e-learning for a global workforce. Workplace e-learning epitomizes a constructivist practice in the workplace; heavily based on European and Western industrialized values; and, remains unconcerned with the culturally specialized adult learning needs and goals of a diverse, global, and multi-facetted, cohort of adult learners. Looking primarily at the constructivist turn in distance education, perspectives of epistemology, ontology, and pedagogy, are referenced that support this trend. The universalizing ramifications of this hypermedia- centred, constructivist trend in workplace e-learning for workplace adult education and training are concerning for a global and diverse cohort of adult learners, who will come to represent the workforce in the future. Technique is increasingly used as the omnibus answer for all learners’ needs and goals. ‘Technology’ increasingly replaces epistemology and ontology as the singular perspective for authentic learning. Some of the unseen, conformist, and persuasive effects of technology, constructivism, and instructors, are now problematized for a global workforce.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.027 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".