Technology, Innovation and Access to Justice
Bibliographic record
Abstract
While legal technology may bring efficiency and economy to business, where are the people in this process and what does it mean for their lives? Brings together leading judges, academics, practitioners, policy makers and educators from countries including India, Canada, Germany, United Kingdom South Africa and NigeriaIncludes contributions from Roger Smith, Dory Reiling, Christian Djeffal, George Williams and Odunoluwa LongeOffers a dialogue between theory and practice by presenting practical and reflective essays on the nature of changes in the legal sectorAnalyses technological changes taking place in the legal sector, situates where these developments have taken place, who has brought it about and what impact has it had on society Around four billion people globally are unable to address their everyday legal problems and do not have the security, opportunity or protection to redress their grievances and injustices. Courts and legal institutions can often be out of reach because of costs, distance, or a lack of knowledge of rights and entitlements and judicial institutions may be under-funded leading to poor judicial infrastructure, inadequate staff, and limited resources to meet the needs of those who require such services. This book sets out to embed access to justice into mainstream discussions on the future of law and to explore how this can be addressed in different parts of the legal industry. It examines what changes in technology mean for the end user, whether an ordinary citizen, a client or a student. It looks at the everyday practice of law through a sector wide analysis of law firms, universities, startups and civil society organizations. In doing so, the book provides a roadmap on how to address sector specific access to justice questions and to draw lessons for the future. The book draws on experiences from judges, academics, practitioners, policy makers and educators and presents perspectives from both the Global South and the Global North.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.031 |
| Scholarly communication | 0.016 | 0.018 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".