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Record W7095810978

Reform of Severance Pay Law Statements and Comments

2006· article· en· W7095810978 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsnot available
Fundersnot available
KeywordsSeveranceUnemploymentQuarter (Canadian coin)Economic shortageImmigrationWageLabour supplyLabour law
DOInot available

Abstract

fetched live from OpenAlex

1.1 Labour market situation Estonia is commonly characterised as a small open economy. The total number of employed persons in Estonia amounted to 586 300 persons in 2005 (data of the Labour Force Survey). The employment rate was 64 % in age group 15-64. The unemployment rate in the third quarter of 2006 dropped to 5.4%, which is the lowest level in the last decade. Employment situation has steadily improved over the last 5 years (starting from 2000), backed by strong economic growth. High economic growth rates – in a range of 7-8 % annually over the period 2000-2004 and reaching 10.5 % in 2005 – have recently lead to a shortage of labour force. Considering the relatively strict immigration rules towards third country nationals and still relatively low attractiveness for intra-Community labour migration, this has resulted in a high competition for labour between companies and has fuelled wage growth in last years. However, recent data (after 2001) on labour turnover is lacking. Masso et al (2004) estimated that gross job flows (job creation and destruction) in 1995-2001 amounted to nearly 25 % of total employment per year. This would mean about 70 thousand new jobs created annually and about the same number destroyed. Higher jobs flows were observed in micro firms employing less than 10 employees and

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.905
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.290
Teacher spread0.277 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2006
Admission routes1
Has abstractyes

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