Bibliographic record
Abstract
In order to find out the causes of universities’ waning popularity as a place of work, the researcher sets the following tasks: to analyze specific features of an academic career to determine at which stage it starts to lose its appeal; to reveal influences in choice of postgraduate courses as an alternative to introduction to the labour market, as well as to reveal influences in choice of a university as a place of work; to evaluate advantages and disadvantages of taking postgraduate courses and working at a university. The researcher conducted 27 semi-structured inter views with the facult y and postgraduates in th ree Russian higher education institutions and one Canadian one: the National Research University “Higher School of Economics”, Moscow State University of Economics, Statistics and Informatics, Siberian Federal University (Krasnoyarsk) and University of Winnipeg (Winnipeg, Canada). On the basis of the findings maps of career lines are produced as patterns of changes in terms of positions (job positions or geographical ones) during a person’s job cycle; the research also revealed types of careers followers of which are of potential interest for Russian universities in terms of professional personnel reinforcement. The researcher found that motivation to take postgraduate courses is not limited by an interest to scientific work but is mostly connected to alternative objectives (like achieving a certain status, draft evasion) or to absence of any definite goal (reluctance to leave the university because of an attachment to it, a sense of discomfort because of the necessity to search for a job outside it). It is shown in the article that on the whole the academic career structure in Canada is similar to that in Russia, but perception of advantages and disadvantages of a work in an academic setting is different for each country.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.000 | 0.001 |
| 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 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".