Bibliographic record
Abstract
In recent years many of us in the field of adult literacy and numeracy have become used to grieving the loss of university based teacher development programs and centres promoting research, professional development and debates in our field. Eighteen months ago, we learnt of the closure of the Centre for Literacy in Montreal, and twelve months ago, the effective closure of the National Research and Development Centre for Adult Literacy and Numeracy in the UK, both of which made major contributions to promoting and giving public access to resources, research findings and policy debates in the field of adult literacy and numeracy. Each year a few more researchers in the field ‘retire’ from their institutions, and while many are remaining active in publishing research, there is a sense of fear about who and what will be left in our field when they decide to really retire!
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 | 0.006 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.011 | 0.013 |
| Insufficient payload (model declined to judge) | 0.044 | 0.041 |
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".