Skills in the Knowledge Economy: Changing Meanings in Changing Conditions
Bibliographic record
Abstract
In the broad field of industrial and employment relations, issues concerning skills and skill development have come to occupy an increasingly significant place in recent years.Shifting the focus from 'training' and 'vocational education' to 'skills' and 'skill development' has opened a broader analysis of a range of work and labour-related phenomena in which skills, knowledge and learning are implicated: the sources of competitive advantage for different economies and firms, the operation and functioning of labour markets, the labour process and the organization of work, the experience of work and the dynamics of power at work and across the economy.This increasing academic interest in skills also reflects the growth of policy and practice concerns at national, industry, organizational and individual levels.National policy concerns in many OECD countries have been motivated by the recognition that cultivating advanced skills is critical to the capacity of industrialized economies to secure competitive advantage and accelerate the move to a 'knowledge economy'.Many individual industries have come to see
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.023 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".