Bibliographic record
Abstract
According to UNESCO statistics, 10 million of the world's 600 million students study at a distance. Theoretical Principles of Distance Education seeks to lay solid foundations for the education of these students and for the structures within which they study. As a more industrialised form of education provision, distance education is well adapted to the use of new communication technologies, and brings to education many of the strengths and dangers of post-industrialism. The central focus of the study of distance education is the placing of the student at home or at work and the justification of the abandonment in this form of education of interpersonal, face-to-face communication, previously considered to be a cultural imperative for education in both east and west. This book explores the problems that distance education poses to the theorist, bringing together an international team of distance educators to address these issues for the first time in a systematic way. The team comprises theoreticians, administrators, experts in educational technology and adult education, experts in learning from video machines, from computers and other forms of technology. Contributions from Italy, and Scandinavia contrast with viewpoints provided by scholars from the US, Canada, Australia, and the UK.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.015 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.016 | 0.010 |
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".