JUDGING THE JUDGES: REVIEWING THE 2025 JUDICIAL EXPERIENCE MANDATE AMID PERSISTING COMPETENCY GAPS AND JUDICIAL ERRORS IN THE INDIAN JUDICIARY
Bibliographic record
Abstract
ABSTRACT This article presents a critical examination of the 2025 Supreme Court ruling that necessitated at least three years in practice before one is eligible to be appointed as a Civil Judge (Junior Division) to effectively solve three major issues raised by the people in regards to incompetence, delays, and irrationality within the lower judiciary in India. The key goal is to investigate whether the required experience is actually relevant to increasing judicial competence and is only a ceremonial obstacle or is the investigated issue influenced by the wider structural and constitutional issues defining Indian judiciary performance. By analysing constitutional provisions, court decisions, and practices in such jurisdiction as the UK, USA, and Canada, the article concludes that judicial experience is not the sole guarantee of competence in the judiciary. These main findings indicate that even highly experienced judges continue to deliver biased or retrogressive rulings as a result of systemic lack of training; monitoring and remedial action; constitutional awareness and inclusiveness. These gaps are compounded by lack of review of judicial performance on a periodic basis and lack of effectiveness in post-appointment training, both of which contribute to reduce the integrity and accountability of the judicial system. The article states that while the 2025 mandate is a step in the right direction that is commendable, it is insufficient by itself. Competence in judges should be construed in a more comprehensive manner by including the clarity of ethics, analytical ability to interpret, compassion, and lifelong study. In order to rebuild the confidence of people as well as constitutional integrity, it is essential that the Indian judiciary needs to institutionalize transparency in its appointments, appraisals and long-term training based on constitutional morality and social justice. Keywords – Competences, Constitutional Morality, Judicial Integrity, Guardian.
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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 | 0.021 | 0.075 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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".