Bibliographic record
Abstract
Compared to other European countries, the employment rate of older workers in Belgium is rather low. This paper argues that one of the most relevant factors underlying the problems of this low employment rate in Belgium is the social policies directed at older workers. Indeed, when unemployment became a widespread phenomenon in the1970s and 80s, early-retirement schemes were designed to alleviate the financial implications on an aging workforce. The government encouraged anyone over 50 to leave the labour market through early retirement schemes, unemployment payment programs, medical retirement, and career breaks. These practises were based on a wide consensus of government, business, and workers.However, for some years now, international organizations have been concerned about the viability of pension systems and their ability to achieve their objectives. In recent years, different factors have led policy makers to rethink this policy. But changing the trend and keeping people on the job has proven more difficult than foreseen. The transformations of public policies begun at the dawn of the 21st century radically changed the balance between the state, workers, and employers, who had all previously seen early retirement as favourable. This paper also tries to show how early retirement is not simply a desire to escape, but can also be explained as an aggression against the person by the labour market. Leaving professional life early thus seems more to be a case of necessity, in fact not a choice at all, but an obligation, or even a sacrifice, and must be seen in the perspective of professional duties and their evolution.
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.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".