Empirical Study of Employment Arrangements and Precariousness in Australia
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
Much research on precarious employment compares permanent workers with one or two other broadly-defined employment categories. We developed a more refined method of examining precariousness by defining current employment arrangements in terms of job characteristics. These employment arrangement categories were then compared in terms of socio-demographics and self-reported job insecurity. This investigation was based on a cross-sectional population-based survey of a random sample of 1,101 working Australians. Eight mutually exclusive employment categories were identified: Permanent Full-time (46.4%), Permanent Part-time (18.3%), Casual Full-time (2.7%), Casual Part-time (9.3%), Fixed Term Contract (2.1%), Labour Hire (3.6%), Own Account Self-employed (7.4%), and Other Self-employed (9.5%). These showed significant and coherent differences in job characteristics, socio-demographics and perceived job insecurity. These empirically-supported categories may provide a conceptual guide for government agencies, policy makers and researchers in areas including occupational health and safety, taxation, labour market regulations, the working poor, child poverty, benefit programs, industrial relations, and skills development.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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