A COMPARISON BETWEEN THE LABOR MARKET TRENDS IN THE EUROPEAN AND ITALIAN BANKING SECTORS: THE IMPACT OF DIGITAL TRANSFORMATION AND THE RELATED NEED FOR INVESTING IN THE HUMAN FACTOR
Bibliographic record
Abstract
In the last thirteen years, the population of bankers in the Euro area has fallen by half a million. In Italy, the phenomenon of setbacks has been similarly dramatic, with a reduction of 70 thousand of jobs in the same period. The rationalization process taking place in the banks of the Euro area has also implied a continuous decrease in the number of branches. The driver of contraction in the banking industry's labor size and territorial presence is to be found in the change in work organization, business model, and corporate strategy consequently to the digital transformation. Banks are concerned with planning constant reductions in the workforce over time, but not with reconverting staff or updating their competencies. The digital competition requires investments in architectures and processes, but for real digital sustainability, it is nonetheless crucial to invest in the adequate sizing of the human factor and related skilling paths.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".