Bibliographic record
Abstract
Professor John Biggs, elsewhere in this JALT, expresses alarm at the gaudy ubiquity of university education, noting a consequent decline in the craft schools of old. As he puts it: We have wound down vocational and technical education and broadened university courses to take in some of the technical content previously taught in technical colleges. A massive mistake, leaving us with … overcrowded and downgraded universities. I can assert – on the basis of 25 years as a university teacher and another quarter of a century in mainstream journalism – that his argument makes considerable sense. In semi-retirement (and working part-time as a newspaper sub-editor), I am able to reflect with some authority on what universities can achieve and what they are less equipped so to do when it comes to the craft of journalism. ‘Craft’ is the term, I feel, that best describes it, for it cannot truly claim to be a profession as its practitioners do not require any specified qualification or formal registration.
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 | 0.007 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.030 | 0.030 |
| Insufficient payload (model declined to judge) | 0.045 | 0.016 |
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".