The Anxiety-Provoking Risks of Performance Management and Its Alternative Solutions in the Banking Environment
Bibliographic record
Abstract
The theory of performance has a unique character as it has allowed the creation of large organizations. It borrows from economic theory the criteria of effectiveness and efficiency. Performance theory itself has a sound foundation, particularly, financial and accounting ones without taking into account its global field of investigation: the organization and the man. In other words, this part of psychology acts and interacts with the organization. This article pursues four main objectives. First, it reminds the central elements of the theory of performance regarding the “capabilities” of “stakeholders.” Second, it aims to identify the factors of performance failure caused by a lack of consideration of global criteria to build a coherent model of optimal management. Third, it maps the risks caused by defects, differences, and gaps in performance management. Finally, it tries to provide an alternative plausible solution to establish more effective performance management. The primary domain is management science while the input from psychology remains limited and applicable only to specific elements such as psycho-social phenomena.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".