Bibliographic record
Abstract
This issue of IRRODL contains papers from Brazil, Greece, Sri Lanka, Canada and the US, and reviews of distance education developments in Africa, Asia, and the Caribbean. A new world of distance education (DE) is coming together in the developing world, as old media such as radio and the telephone merge with each other and the Internet to form wholly original interactive partnerships. So I now offer you a new piece of jargon, coined to pay respect to the creative return to older DE media: ‘paradigm rollback’ – you heard it here first! This odious but quite typical piece of verbiage signifies “a shift back to an idea whose time has come,” as in the case of DE technologies supplanted for a while by the promise that the Internet would do the job better. I just looked the term up on Google, and find only one reference to it so far – in the conference presentation where I coined the term a week ago! Let’s see how many references there are to ‘paradigm rollback’ a few months from now among those for whom jargon is all . . .
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 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 | 0.009 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.008 | 0.015 |
| Insufficient payload (model declined to judge) | 0.053 | 0.030 |
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".