Non-standard employment forms: world experience of development (on the example of volunteering and volunturism)
Bibliographic record
Abstract
The article discusses the world experience in the development of non-standard forms of employment (NZF) on the example of volunteering and volunteerism, namely: in the UK, Ireland, Spain, Italy, Canada, Latvia, Lithuania, Luxembourg, Macedonia, Germany, Norway, South Korea, Poland, Portugal , Romania, the USA, Hungary, France, Croatia, the Czech Republic, Sweden, Japan, etc., which are inherent in the general laws of economic development, uniform rules and patterns of activity, and features related to the specifics of providing volunteer and volunteer services. Under the influence of the latter, the regularities of the development of the NZF volunteering and volunteerism acquire specific features that allow them to be determined by both the expansion of employment of the population, and tourism activities. Volunteering and volunteerism arose in the process of transformation of employment in modern conditions and are a symbiosis of innovative forms of social and labor relations and forms of precarious work.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.018 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.000 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".