Indépendance ou employabilité : comment le genre influence-t-il les motivations des jeunes à entreprendre une mobilité temporaire ?
Bibliographic record
Abstract
Although educational temporary mobility, such as language stays or student exchanges, are increasingly popular among young adults, participation rates remain uneven. But whereas previous academic studies have identified gender as an important factor—young women participate more than young men—little has been written on the mechanisms behind this disparity. This article uses a mixed-method triangulation approach to analyze the impact of gender on motivational factors influencing the participation of young adults in travel programs. Using a large-scale survey of young Swiss adults (ch-x survey), we validate a set of hypotheses based on fourteen interviews conducted with male and female students attending the University of Lausanne. We begin by comparing the motivational factors influencing female and male students. Then, we consider the motivating factors influencing young adults with different educational backgrounds. The results highlight two critical dimensions of how gender affects the decision-making process: first, the acquisition of mobility capital in support of employability and, second, the increased independence gained through temporary mobility.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".