Bibliographic record
Abstract
Career management over the lifespan has become increasingly important due to the extension of working lives in most developed and many developing countries. The extension of working lives, in fact, is a politically enforced phenomenon as a reaction of more or less constantly low birth rates and increased life expectancies that have caused global population ageing. In the last decade, several developed countries have introduced new regulations to gradually increase retirement age (i.e., eligibility age of receiving a public pension) from 65 to 67 in the mid-term future (e.g., Australia, Canada, Denmark, France, Germany, Greece, Israel, Netherlands, Poland, Spain, or the USA) (Organization for Economic Cooperation and Development [OECD] 2013). Further, plans to increase the retirement age even beyond 67 exist in some countries, such as in the UK, which plans an increase of retirement age to 68 between 2044 and 2046 (OECD 2013). In addition to the normal retirement age, some countries have implemented a policy to allow people, who have contributed for a certain time (e.g., 40 years in Greece or 45 years of minimum contributory record in Germany), to receive a public pension before retirement age (e.g., starting from 62 in Greece or 63 in Germany) (OECD 2013; German Statutory Pension Insurance Scheme 2015). These new regulations will have a critical impact on the labour market in the future.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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; both teacher heads agree on what is shown here.
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".