Bibliographic record
Abstract
This section provides an overview of key labour market data in Scotland and contrasts these with both UK performance and changes over time. These data are from a range of the latest labour market data for Scotland and the UK, to August 2014. The Scottish unemployment rate stands at 5.5%, below the UK rate of 6.0%. The employment rate in Scotland is 73.9%, with the UK figure 73%. In 2014 the number of people in employment in Scotland has reached the highest on record. Growth in employment, however, is still sustained by part-time workers and self-employment. Wages have failed to show sustained growth suggesting that traditional wage setting mechanisms remain impaired. Thus, despite the positive signs of recovery in the Scottish labour market, there is still remaining slack and possibly even wider structural issues. Recent trends and statistics The latest comparable figures on the labour market between Scotland and the United Kingdom in the quarter to October 2014 are summarised in Table 1. Labour Force Survey (LFS) data show that in the quarter to October 2014 the level of employment in Scotland rose by 35 thousand, to 2,611 thousand and over the year by 52 thousand. For the same period, UK employment rose by 46 thousand and 736 thousand respectively. The Scottish employment rate (16 – 64) – i.e. those in employment as a percentage of the working age population – was 73.9%, up 1.3 % from one year earlier. For the same period the UK employment rate was 73.0%, up 1.5 % compared to a year earlier. Scottish unemployment, in the quarter to October 2014, fell by 40 thousand to 151 thousand, a fall of 52 thousand over the year.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.345 | 0.172 |
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".