Bibliographic record
Abstract
Topicality of the research subject is proved by the fact that during the last two decades new forms of employment kept developing, among which digital work takes the leading position as it is a dynamic and flexible form of basic and additional employment. Changes on Russian labour market taking place in the context of passing to platform employment lead to the necessity to investigate structural changes. The article provides findings of the economic and statistic research on the structure of platform-employed people in Russian economy. The choice of basic period of time for the research is stipulated by the fact that since the 1st quarter 2022 statistic records include the indicator of those platform-employed. Investigation of 1D simple structures made it possible to draw up social and demographic profile of platform-employed resident of Russia and make conclusions about its alterations during a set period of time. By analyzing structural shifts results were obtained that show a drop in certain sections by a number of characteristics, such as gender, age, education and its level, place of residence. Inessential changes in structures being studied were found. Research findings dealing with structure of platform employment can be used as a basis for elaborating employment policy aimed at creation of stable and flexible system promoting economic development in conditions of fast changing labour market.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".