Evaluating the Prevalence and Distribution of Envelope Wages in the European Union: Lessons from a 2013 Eurobarometer Survey
Bibliographic record
Abstract
The aim of this article is to evaluate the prevalence and distribution in the European Union of a little discussed illegitimate employment practice whereby employers pay their formal employees both an official declared salary and an undeclared ‘envelope’ wage so as to evade the full tax and social security dues owed. To do this, a 2013 Eurobarometer survey involving 11,025 face-to-face interviews with formal employees in the 28 member states of the European Union is employed. The finding is that one in 33 employees received envelope wages during the 12 months prior to the survey, amounting on average to one quarter of their gross annual wage. Employers in East-Central and Southern European countries, and in smaller businesses, are more likely to use this fraudulent wage practice which is concentrated amongst weaker more vulnerable employee groups such as younger, skilled and unskilled manual workers, those facing financial difficulties and those with fewer years in formal education, but interestingly, also professionals and those travelling for their jobs. The paper then discusses possible causes as well as the policy options and approaches for tackling this illicit wage practice.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".