Nonstandard Career Trajectories and Their Various Forms
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
A sample of 124 participants (62 men, 62 women) was used in this qualitative research study of people having experienced nonstandard work for the last 3 years. Those participants were met for individual semistructured interviews of approximately 2 hours in length. On the basis of a content analysis with the use of the NUD*IST analysis software, 4 trajectories and 14 subtrajectories were identified: ascending (constant progression, final recovery, uncertain outcome), descending (sudden drop, caught in a trap, long descent, noninsertion), interesting maintenance (accepted job insecurity, project continuity, new project), and uninteresting maintenance (bogged down, leitmotif, adapted, and 180 degrees). The descending and uninteresting maintenance trajectories were predominant, comprising more than two thirds of the participants. Differences were found between genders, age groups, and educational levels. The results are discussed with respect to the scientific literature and to the differences that were observed.
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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it