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Record W7065500215

EEO Review : adapting unemployment benefit systems to the economic cycle - Malta

2011· report· en· W7065500215 on OpenAlexaboutno aff

Bibliographic record

VenueOAR@UM (University of Malta) · 2011
Typereport
Languageen
FieldPhysics and Astronomy
TopicRadiation Detection and Scintillator Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsUnemploymentSocial securityMaltesePovertyQuarter (Canadian coin)Social assistanceSocial protectionSocial insurance
DOInot available

Abstract

fetched live from OpenAlex

It is commonly perceived that over the past decades, Malta has created a generous welfare state, including among others, free education and healthcare, adequate pensions and safety nets that result in relatively low poverty levels. Indeed, the Eurostat Household Budgetary Survey revealed that in 2008, 14 % of the Maltese population was at risk of poverty, in comparison to the higher EU-27 average of 17 % (Times of Malta, 2010). Despite this, in 2009, expenditure on social protection benefits amounted to ‘only’ about a fifth of Malta’s Gross Domestic Product, a figure considerably lower than that of the EU average of about a quarter of the GDP in 2008 (National Statistics Office, 2011). However, whereas between 2005 and 2008, social protection benefits in the EU-27 grew by 9.5 %, Malta registered an increase of 22.3 %. In line with the fact that Malta has a relatively low unemployment rate, in 2008, unemployment benefits only amounted to 2.7 % of the total expenditure on social protection, when compared to the 5.2 % of the EU-27. Out of the various types of social benefits, in 2009, unemployment benefits registered the highest increase (of EUR 5.1 million) when compared to 2008, mainly due to the increase in unemployment in 2009. The unemployment benefit system in Malta is regulated by the Social Security Act (Government of Malta, 2011b). The Act provides for two main schemes, the contributory and the non contributory schemes. The contributory scheme is universal, covering all strata of society. All workers pay weekly contributions to their national insurance in order to be entitled to unemployment, sickness and retirement benefits. On the other hand, the non contributory scheme, originally meant to cater for persons living below the poverty line, is based on a financial means test. Unemployment benefits provided under the Social Security Act are partly funded by social security contributions levied upon employed persons and employers, and partly funded by the Government through tax revenues. The rates paid by employees and employers vary according to their level of income. Unemployment benefits are awarded by the Social Security Department (SSD). However, in order to claim such benefits, a person must be registered as available for, capable of and be seeking full time employment, in the Employment Register kept by the Employment and Training Corporation (ETC). In its role as Malta’s public employment service organisation, the ETC is in charge of helping those seeking employment through job-matching processes and the provision of training and work experience programmes. Unemployment benefits are payable for a maximum period of 156 days, and must not exceed the number of contributions paid. To re-qualify for such benefits, a person must be in insurable employment for 13 weeks from the last day of his/her entitlement for such benefits (Zerafa, 2007). When the 156 days run out, unemployed persons can apply for the long-term benefits known as ‘unemployment assistance’, which they continue receiving throughout the whole unemployment period. Besides, unemployed persons may be entitled to an increase in unemployment assistance under special circumstances. Apart from a few exceptions, all unemployment assistance is stopped when employment, even if on a part-time basis, is found. All those in receipt of unemployment assistance are also eligible for free medicines, full children’s allowance, and energy benefit.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.643
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.033
GPT teacher head0.236
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

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