The Australian Veterans' Scholarship Program (AVSP) Through a Career Construction Paradigm
Bibliographic record
Abstract
In Australia, 6000 military personnel leave the military each year, of whom at least 30% become unemployed and 19% experience underemployment, figures five times higher than the national average (Australian Government 2020). Believed to be one of life's most intense transitions, veterans find it difficult to align their military skills and knowledge to the civilian labour market upon leaving military service (Cable, Cathcart and Almond 2021; AVEC 2020). // Providing authentic opportunities that allow veterans to gain meaningful employment upon (re)entering civilian life raises their capability to incorporate accrued military skills, knowledge, and expertise. Despite acknowledging that higher education is a valuable transition pathway, Australia has no permanently federally funded post-service higher education benefit supporting veterans to improve their civilian employment prospects. Since World War II, American GIs have accessed a higher education scholarship program (tuition fees, an annual book allowance, monthly housing stipend) (Defense 2019). A similar offering is available in Canada, the UK, and Israel. // We are proposing that the AVSP would be the first comprehensive, in-depth study investigating the ongoing academic success of Australia's modern veterans as they study higher and vocational education. It consists of four distinct components: // Scholarships: transitioning/separated veterans apply for one of four higher education scholarship options (under/postgraduate): 100% tuition fees waived // $750/fortnight living stipend for the degree duration // 50/50 tuition/living stipend // Industry-focused scholarships. // Research: LAS Consulting, Open Door, Flinders University, over seven years, will follow the scholarship recipients to identify which scholarship option is the most relevant/beneficial for Australian veterans. The analysis of the resultant quantitative and qualitative data will demonstrate that providing federal financial support to student veterans studying higher education options: Improves the psychosocial and economic outcomes for veterans // Reduces the need for financial and medical support of participants // Reduces the national unemployed and underemployed statistics for veterans // Provides a positive return of investment (ROI) to the funder // May increase Australian Defence Force (ADF) recruitment and retention rates // Career Construction: LAS Consulting will sit, listen, guide, and help build an emotional connection around purpose, identity, education and employment opportunities back into society. So, the veteran can move forward, crystalise a life worth living, and find their authentic self, which is led by their values in the civilian world. // Mentoring: Each participant receives a mentor throughout their academic journey.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".