Legitimacy and online proceedings: Procedural justice, access to justice, and the role of income
Bibliographic record
Abstract
Abstract Courts have long struggled to bridge the access-to-justice gap associated with in-person hearings, which makes the recent adoption of online legal proceedings potentially beneficial. Online proceedings hold promise for better access: they occur remotely, can proceed asynchronously, and often rely solely on written communication. Yet these very qualities may also undermine some of the well-established elements of procedural-justice perceptions, a primary predictor of how people view the legal system's legitimacy. This paper examines the implications of shifting legal proceedings online for both procedural-justice and access-to-justice perceptions. It also investigates the relationship of both types of perceptions with system legitimacy, as well as the relative weight these predictors carry across litigant income levels. Drawing on online traffic court cases, we find that perceptions of procedural justice and access to justice are each separately associated with a litigant's appraisal of system legitimacy, but among lower-income parties, access to justice is a stronger predictor, while procedural justice dominates among higher-income parties. These findings highlight the need to incorporate access-to-justice perceptions into existing models of legal legitimacy.
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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 | 0.006 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".