Bibliographic record
Abstract
As well as a sharp rise in unemployment, the economic and financial crisis saw a significant increase in the number of people outside the labour force, i.e. individuals who are currently not classified as unemployed but are not in employment and are available for work. In this Letter we construct a new measure of labour utilisation - the Non-Employment Index (NEI) - that takes into account this potential additional labour supply. The index distinguishes between groups like short-term and long-term unemployed, discouraged workers and passive job seekers, factoring in how likely each group is to transition to employment. By including tailored weights that take into account persistent differences in each group’s likelihood of regaining employment, the NEI is arguably a more comprehensive measure of labour market conditions than the standard unemployment rate. Our estimates show that, as of the last quarter of 2016, the non-employment rate (including part-time underemployed workers) had declined to 9.4 per cent at the end of 2016 - significantly below its crisis peak but slightly higher than the standard unemployment rate. Our analysis suggests that there may be some scope for the unemployment rate to fall further before significant wage pressures emerge, but labour supply conditions are tightening as a strong recovery continues.
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How this classification was reachedexpand
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 | 0.000 |
| Science and technology studies | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".