Perceptions Of The Characteristics Of The Social Contract In Management In Romania Before 1989. Exploratory Case Study In The Romanian Automobile Industry
Bibliographic record
Abstract
Defined as set of tacit norms and laws existing in a given society in relation to what is considered acceptable and tolerable in the employment relationship, the social management contract (SMC) has recently proved to be an interesting tool for an contextualized study of the relationship that the employee develops with his employer. This paper is based on the research results obtained by the author during her doctoral thesis at the Universite du Quebec a Montreal (Canada). In this thesis, we propose to study how the former social contract of Romania (that before the fall of communism) impregnates the current social contract in this country. To compare it with the new social contract, we analyzed the features of the old Romanian social contract. This analysis, which makes the object of this paper, was carried out in a constructivist approach, based on 39 interviews conducted in two companies of the automobile industry of the region of Sibiu, Romania. We have thus identified three main categories of characteristics of the old social contract (which we characterized as paternalistic): protection / security, hierarchy and community spirit. We will detail each of these characteristics in this paper. The theoretical and practical contributions of our study on the SMC before 1989 and its limitations will also be mentioned in the communication.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".