Modernising Staffing and Court Management Practices in Ireland
Bibliographic record
Abstract
The effectiveness and efficiency of the justice system are important factors for strengthening citizens' trust, ensuring the proper functioning of markets, and driving inclusive growth.The certainty of judicial decisions, the accessibility of judicial services, effective contract enforcement and secure property rights are demonstrated drivers of economic activity and foreign direct investment.Effective justice institutions are critical for protecting democratic values and strengthening the social contract between citizens and the state.Acknowledging this, Ireland has launched an ambitious strategy to build a more inclusive, efficient and sustainable justice sector.Irish citizens recognise these efforts: Ireland is one of the OECD countries with a higher percentage of citizens trusting their government and courts, as highlighted in the recent OECD Survey on the Drivers of Trust in Public Institutions.As part of the OECD work on accessible, effective and efficient justice institutions, this study seeks to support these efforts by analysing the judicial workforce and relevant support structures and processes currently employed by the Irish courts.In particular, the study aims to contribute to the deliberations of the Irish Judicial Planning Working Group, which was established to identify reform initiatives and evaluate staffing needs to enhance the efficient administration of justice over the next five years.The study methodology calculated judicial full-time positions in Ireland using the number of filings and the average amount of time required to manage distinct case types (case weight), divided by a judge's working hours throughout a year.The case weights were obtained through a judicial time study and verified through Delphi vetting estimates across the Irish Court of Appeals, the High Court, the District Courts and Circuit Courts.The study also included stakeholder interviews helped identify options to enhance the efficiency of court procedures and infrastructure.It benefited from comparable data and peer reviews from OECD countries including Australia, Canada, the Netherlands, the United Kingdom, and the United States.Ireland has the potential to shine as an international dispute-resolution hub.To do so, Ireland needs to continue investing in the court reforms that lie at the heart of its 2020 Programme for Government, while supporting stronger leadership in pursuing these reforms in a way that enhances trust and collaboration among justice sector stakeholders, as well as the broader public.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".