The next mission: Inequality and service‐to‐civilian career transition outcomes among 50+ military leavers
Bibliographic record
Abstract
Abstract We examine the Service‐to‐Civilian career transition for Military leavers aged 50 and above (50+). The exit age of our sampled group means that it is more likely that they hold senior‐ranked positions across both Officer and Soldier career pathways. Despite both groups having access to similar transition opportunities and resources, we find that their work‐lives are underpinned with economic, social, and structural inequality. This inequality has substantive effects on their employment transition outcomes. Our focus group data suggest that Soldiers have unequal access to formal (e.g., Career Transition Partnership programmes) and informal (e.g., social networks) transition support resources compared to Officers. Employing a structural equation modelling approach to analyse 183 survey responses, we found that Soldiers are more likely to apply for, and subsequently take, civilian work that is below their skills level. In turn, Soldiers are significantly less satisfied with their civilian work than Officers.
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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 | 0.001 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".