Bibliographic record
Abstract
The Adult Literacy and Lifeskills Survey (ALL) is an international comparative study conducted in 2003 to provide participating countries with information about the skills of their adult populations. ALL measured the literacy and numeracy skills of a nationally representative sample of 16- to 65-yearolds from six participating countries (Bermuda, Canada, Italy, Norway, Switzerland, and the United States). Literacy is defined as the knowledge and skills needed to understand and use information from text and other written formats. Numeracy applies to the knowledge and skills required to manage mathematical demands of diverse situations. A second phase of ALL, in which additional countries are collecting data, is currently under way. This will allow for a greater number of country comparisons. ALL builds upon earlier national and international studies of adult literacy. 1 Information from ALL addresses questions such as: • What is the distribution of literacy and numeracy skills among American adults? How do these skill distributions compare to those of other countries? 1 An assessment of young adult literacy was conducted in the United States in 1985, an assessment of the literacy of job seekers in 1991, a National Adult Literacy Survey (NALS) in 1992, and a follow-up
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.267 | 0.084 |
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".