On University Teacher's Non-wage Income and Higher Education Dissimilation LES PROFESSEURS D'UNIVERSITE NON SALARIAUX ET DE DESASSIMILATION DE L'ENSEIGNEMENT SUPERIEUR
Bibliographic record
Abstract
In the current era of knowledge economy, higher education plays an increasingly important role in promoting social development. University teachers’ non-wage income from the commercial lectures, training classes, off-campus part-time jobs and academic activities has grown rapidly. Popularization of university teachers’ profit-making has constantly eroded the essential attribute of higher education, and led to the higher education dissimilation embodied by phenomena such as “transactions between money and knowledge”, “part-time job tendency”, “becoming rich by scientific research” and “abuse of power”. Key words : University teacher; No-wage income; Higher education; Dissimilation Resume Dans le contexte actuel de l’economie du savoir, l’enseignement superieur joue un role de plus en plus important dans la promotion du developpement social. Les professeurs d’universite ‘‘des conferences commerciales, les classes de formation, hors campus emplois a temps partiel et des activites academiques a connu une croissance rapide. Vulgarisation des professeurs d’universiteles revenus non salariaux ‘‘a but lucratif a constamment erode l’attribut essentiel de l’enseignement superieur, et a conduit a la dissimilation de l’enseignement superieur incarne par des phenomenes tels que “les transactions entre l’argent et des connaissances”, “la tendance emploi a temps partiel’’, ‘‘de devenir riche par la recherche scientifique’’et ‘‘ l’abus de pouvoir ’’. Mots cles : Professeur d’universite, Non salarie; L’enseignement superieur; Dissimilation
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".