Неустойчивая занятость: концептуализация понятия и критерии оценки
Bibliographic record
Abstract
The transition of Russia toward a market economy has resulted in public relations’ transformation in social life including social-labour relationships. It has led to the formation and development of new work statuses. On the one hand, it has extended potential for the use of work-force, made labour market more flexible. On the other hand, these changes have shattered socio-economic standing of many employees due to the fact that some work forms lead to income insecurity, full or part deformalization of employer-employee relationships; they increase the risk of dismissal, weaken labour guarantees and infringe rights. Work characterized by these threats and risks is defined as “precarious employment”. Whereas, in socio-economic sciences there are no detailed criteria allowing to classify employment as stable or precarious. Canadian researchers have contributed the most to the solving of this problem C. Cranford, L. Vosko, N. Zhukevich, who have articulated the concept “precarious work” and studied it based on official Canadian statistics. However not all results are suitable for Russia due to certain peculiarities of the Russian model of labour market. G. Standing’s studies of precariat are also of great importance. The article sums up and analyses works of foreign and Russian researchers on precarious work in order to determine main criteria for assessing sustainability of employment in Russia and its regions.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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".