Context, Resources and Strategic Choice: Responses to Labour and Skill Shortages
Bibliographic record
Abstract
Labour and skill shortages are widely reported across most countries. With changing demographics, increasing digitalization and the transition to a green economy, to name but a few factors, concern is mounting about the supply of labour and skills for future demands. As a result, actors in the labour market, such as unions, employers and employer associations, government and civil society organizations are concerned about looming shortages of labour and skills. Several strategies to address such shortages have been identified, but a more detailed engagement is required to fully understand the complex interplay between each strategy and the environment in which it is pursued. Semi-structured interviews were conducted in Ireland with a range of actors who were specifically identified as having expertise and experience in strategies for labour and skill shortages. They reported a range of strategies that involved upskilling, higher pay, better working conditions, flexible work arrangements, use of migrant labour, development of untapped labour pools and provisioning of social goods. Decisions on these strategies had two key determinants: resource availability and the external environment. All actors mentioned a need for social dialogue to engage, explore and consider the wide range of options for dealing with labour and skill shortages.
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.
How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".