Bibliographic record
Abstract
This editorial of December 2021 is written at a time when the world continues to reel from the effects of COVID-19. foreword of issue 13(2) of December 2020 I wrote optimistically that, “it is likely to be well into 2021 before the beneficial influences of vaccines will be felt through the world”. Whilst these influences are being felt the omicron mutation of the virus is spreading and the pandemic continues. There is still much to be done is establishing an equitable sharing of vaccines throughout the world. Working and researching in global contexts affected by the pandemic, Living Educational Theory Researchers continue to contribute their educational knowledge to the professional knowledgebase of education as they ask, research and answer questions of the kind, ‘How do we improve our practice as global citizens as our individual and collective contributions to bringing into being a world of human flourishing?'. The sites of practice of contributors to issue 13(2) highlighted the international reach of Living Educational Theory Researchers with papers from researchers in New Zealand, India, Pakistan, Canada and Bangladesh. The sites of practice of contributors to issue 14(2) include Bangladesh, the Bahamas and Nepal. The two books reviewed are those of Suresh Nanwani researching in the Philippines and Robert Maxwell in 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 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.173 | 0.142 |
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".