Life after higher education : the diversity of opportunities and obstacles in a changing graduate labour market
Bibliographic record
Abstract
From the latter part of the twentieth century and onwards progressively rapid industrial restructuring, technological change and globalization have changed the parameters of employment. Governments’ assessments of the skills required for economic growth and development have driven higher education investment and expansion policies in the UK, as they have internationally. Looking across OECD countries, it has recently been estimated that an average of 40 per cent of young adults are likely to complete undergraduate (tertiary Type-A) education during their lifetime, with graduation rates in European countries ranging from half or more in Finland, Iceland, Poland and Russia to less than a quarter in Belgium, Greece, Estonia (OECD, 2014). Higher education (HE) has become a global industry – part of the ‘knowledge economy’ that it serves – and this is reflected in increasing education-led migration and mobility – both of EU and overseas students to study in UK and of UK students to study overseas.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".