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 main objective of this paper is to investigate the use of earnings spells in LEED as a measure of job tenure. The paper explores the extent to which employment relationships in LEED contain multiple job (earnings) spells and the impact on the tenure distribution if individual job spells, between an employer and employee, are joined together. The study found that one in five jobs (21.1 percent) in LEED, as at March 2006, were repeat spells with the same employer and nearly half (~-1.4 per cent) of repeat - job spells started following a single month of non-employment and only 16.2 percent o f repeat spells occurred after a non-employment period o f over 12 months. Imputing all non- employment periods as employment had a measurable, but not a particularly dramatic effect on the job tenure distribution. For example, the share of job spells with elapsed tenure of 12 months or less falls by only 10 percentage points from -18.1 percent to 38.0 percent. a decline o f around 20 percent. A distinctive pattern among repeat-job spells was for an earnings spell to end in December and for a new spell to begin in February. Around a quarter o fall repeat spells, separated by a single month, start in February, in particular, 63.1 percent of job spells in the education industry fall into this category.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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