The Impact of Extra-Legal Factors on Adjudication: Theoretical and Practical Aspects
Bibliographic record
Abstract
Adjudication is a complex and multifaceted process that involves not only legal but also personal and psychological aspects. In a combination, they can be regarded as the extra-legal affect on specific categories of cases. The issue under studies is relatively new in present-day Ukraine. However, this field of scientific research originated in America at the end of the XIX century. Although it has lost its relevance, today, this issue is gaining popularity again, particularly in the works by both national and foreign scholars, who directly or indirectly reveal it.
 The article under discussion presents the analysis of theories, developed by national and foreign authors. These works trace the tendency to identify the factors that may affect the judges’ decision-making process, both directly (legal experience; political predisposition; intellectual and temperamental traits) and indirectly (overall erudition; family and personal associations, social status).What is more, the author of the article has identified two possible options for a judge to make a decision - by justice and by law. They are by no means related to each other, since not all the decisions, made in compliance with the law, are fair, whereas it is much easier to make fair decisions conform to the letter of the law.
 This research is based on the materials of study carried out in 1914-1916 regarding some New York City magistrate judges, who made different decisions on similar categories of cases. Such a discrepancy again outlines the boundaries of individual relationships that affect the administration of justice.
 In addition to the above, the theoretical material, outlined in the article, is rests on the examples from the court records of Canada and Ukraine. This made it possible to prove and realize that such extra-legal impact does exist today and is ruining the judicial system from inside.Besides, the investigation reveals the ECHR’s position on the issue under study. Relying on specific examples, we have pointed out various manifestations of judges’ bias. In those cases, they were driven by personal views and motives, which, in turn, influenced their final decisions, the latter being subsequently challenged.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".