Bibliographic record
Abstract
The law of the jungle – is this all the future holds for us? Unfortunately, reading some opinion articles we might believe that this is inevitably the case. In 1984, the year in which Gérard Debreu was awarded the Nobel Prize in Economics, he said in le Figaro Magazine that the superiority of liberalism had been proven mathematically, bearing in mind, that just as a few decades earlier, the brilliants minds of the time had also given “scientific” socialism the stamp of approval. Closer to our time, in 2003, the then [French] Finance Minster, Francis Mer, argued on a television programme that a person’s salary was proportional to his value in society. Taken literally, his statement implies that a Managing Director with a salary of 38.8million euros is by far more useful to society than either, a carer, teacher or judge. The facts show that, two decades down the line, the economist and ex-business leader’s comments mirror the current situation to the point that we might believe that market law can harmonize economic efficiency and social justice perfectly.
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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.038 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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; 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".