Minimum Wage and Effects on Unemployment: The Case of Spain and Its Implications on Simpson’s Paradox and Geographical Mobility
Bibliographic record
Abstract
This research explains the effects of the Government’s regular increases in the minimum wages on unemployment in Spain. Using a longitudinal analysis covering the years 2010 to 2023 the research collects data split by gender, age group, and Autonomous Community (AC). The data has been adjusted calculating the minimum wage Mean and Mode values. A negative or inverse correlation between minimum wage variables and unemployment is observed presenting Pearson values between -0.4 and -0.6 in most groups. Also, the research applies a one-way ANOVA test. It shows findings of unemployment reduction, specifically in the categories of young males, even though, the minimum wage in Spain has been regularly increased during the last years, in line with other authors. The aggregated and disaggregated data obtained vary and move in opposite directions confirming in a certain way that the principle of the Simpson’s Paradox could take place here. The research also confirms a relevant Estimated Size Effect (ETA) when comparing Autonomous Communities and their influence on unemployment for 55+ years old people.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".