Integrating jobseekers in the labour market : are the strategies adopted by the German PES applicable to Malta?
Bibliographic record
Abstract
The effects of the international economic recession on Malta have been relatively mild and mostly felt in the automotive and tourism sectors. The economic recovery of Malta, beginning in the last quarter of 2009 increased its momentum in the first quarter of 2010, with the economy growing by 3.4% over the previous year. The growth occurred through a rapid increase in exports, the largest among EU member states in the first four months of 2010. Survey results indicate that a general improvement in business confidence accompanied such economic recovery. Malta‟s employment rate was 55.3% in the first quarter of 2010, when compared to the 54.6% of the same quarter of the previous year. This figure includes the female employment rate of 38.5%, which despite considerable government efforts and a slight increase over the years, is still by far the lowest among EU countries. Among the sectors that recorded a rise in employment between the first quarters of 2009 and 2010 were: wholesale and retail trade repairs (by 9.3%); and health and social work (by 26.4%). On the other hand, among the sectors that experienced a drop in employment were: transport, storage and communication (by 9.4%); public administration, defence and compulsory social security (by 8.1%); and education (by 7%). It is of concern that the ratio of full-time employees declined from 89.3% to 87.2% (equivalent to 140 persons), while the ratio of part-time employment increased from 9% to 10.7% (an increase of 3,160 persons), and the ratio of full-time employment with reduced hours jobs increased from 1.7% to 2.1% (an increase of 722 persons) between the first quarters of 2009 and 2010. The economy appears to be experiencing difficulties in creating new full-time jobs. [Excerpt]
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".