Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The authors study the topic of youth employment in Russian regions through the lenses of both global factors and national institutions. These include the national professional education system as well as personal choice of occupation, university, employer and place of residence. Given that Russia’s regions belong to a single state with common institutions, one language and an otherwise homogenous social structure, this situation provides important insight into what helps young people fully realize their potential and ambitions or, conversely, prevents them from doing so. Professional education is becoming more and more vital for an individual’s career, self-reliance and ability to contribute to the development of the country. However, while selecting a university or an employer, one can be susceptible to negative social experience which can trigger the development of destructive attitudes. The authors look at how this can impact a person’s professional career, which is prone to change given the pace of technological development today. Global networks of people and organisations impact youth employment all over the world, including Russia. This results in widespread remote working, which, in turn, brings highly-skilled vacancies to remote places. Remote working and studying levels out inequality in access to educational and cultural institutions as well as to work that young people find fulfilling. In this context, the article, inter alia, studies the impact of the national “Digital Economy” strategy on youth employment in Russia.
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.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 it