Bibliographic record
Abstract
I cannot count the number of times I have heard the same litany of complaints in the course of my conversations with shopkeepers, artisans, and the directors of small businesses: “Of course, I could expand, take on one or two young workers. But I won't do it. Too expensive. Too complicated.” The center-Right politician Pierre Lellouche, 1998. Things are booming at the moment, but I'll do anything to avoid taking on more workers. A building contractor in Lille, 1999. With the spread of youth unemployment and poverty, the implicit acceptance by the popular classes and a good part of the middle classes of a certain period of personal sacrifice in exchange for a better future for the younger generation, seems to have evaporated. Sociologist Jean-Marie Pernot, 1998. The spoiled children of May 68 [those born during the 1940s] have traversed the crisis [the crisis of unemployment of the 1980s–90s] practically unscathed, as if they still lived under the sign of the trente glorieuses . The growth escalator stopped as soon as the generation born after 1955 tried to get on board. Bernard Préel, middle-aged author of the book, Le choc des générations (2000). Millions of young people remain trapped in the unemployment and underemployment ghetto. Hundreds of thousands of youth of North African descent, especially young women, have never had the chance to work.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".