Employment restructuring and the search for flexibility: The case of non-standard employment in Ireland
Bibliographic record
Abstract
The study is based on the Irish version of the 2001 International Social Survey Programme (ISSP) Work Orientations module, which is a national representative sample of the adult population. The results show that non-standard employment in its various forms accounted for almost half of the respondents in the study. Self-employment was the largest category (18%) followed by permanent part-time (10.6%), temporary/seasonal (9.6%) and contract employment (8.3%). Overall the analyses portray a picture of diversity on many levels, from the nature of the jobs themselves, the people in the jobs and the outcomes of such employment and in particular the economic implications. From an economic perspective while standard workers were in a superior economic position relative to their non-standard counterparts, the extent of difference varied with the economic indicator in question and/or the specific comparison between standard and non-standard forms of employment. However, in general respondents in non-standard work arrangements had less opportunities (in terms of income and career mobility), rewards and resources than their standard counterparts which translated into a poorer economic position. In addition to the economic implications there are also clear gender issues inter-woven into the many aspects of non-standard employment, as also are life course and institutional factors. This thesis examines many dimensions of employment flexibility but predominantly focuses on non-standard employment or contractual flexibility. It is a broad and comprehensive examination of non-standard employment in Ireland and examines the extent of such employment, the nature and social bases of non-standard employment, the relationship between non-standard employment and other forms of employment flexibility, and the implications of non-standard employment. Overall, based on the results of this study, non-standard workers in Ireland in general fared better in comparison with studies based non-standard workers in less regulated labour markets such as the USA and Canada. Non-standard employment in an Irish context is a diverse experience and the impact of non-standard employment varies considerably depending on job type, gender and the outcome in question.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".