Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Covid-19 crisis will have fundamental impacts on the future of working lives. Daily forecasts predict a depressing picture for the working-age population, both in the UK and abroad. This makes it difficult to identify positive outcomes from the crisis for work, life, and welfare. Poor government planning and decision-making concerning health and economic responses have further added to the problems, rather than resolving them. This is exemplified by the lack of clarity, speediness, and sufficiency of many of the schemes devised to help employees, employers, and those unemployed. Increases in sales and recruitment by tax-avoiding Amazon (+2.53% according to market watch in the first quarter of 2020) provide just one example of the economic and labour market effects of this crisis being unfairly distributed. While online sales and delivery companies, such as Amazon, food production and supply organisations, internet service providers and TV and film streaming companies are likely to be among the big winners from the current crisis, there will also be many losers.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it