Unintended Consequences: The Regressive Effects of Increased Access to Courts
Why this work is in the frame
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Bibliographic record
Abstract
Small claims courts enable parties to resolve their disputes relatively quickly and cheaply. The court's limiting feature, by design, is that alleged damages must be small, in accordance with the jurisdictional limit at that time. Accordingly, one might expect that a large increase in the upper limit of claim size would increase the court's accessibility to a larger and potentially more diverse pool of litigants. We examine this proposition by studying the effect of an increase in the jurisdictional limit of the Ontario Small Claims Court. Prior to January 2010, claims up to $10,000 could be litigated in the small claims court. After January 2010, this jurisdictional limit increased to include all claims up to $25,000. We study patterns in nearly 625,000 disputes over the period 2006–2013. In this article, we investigate plaintiff behavior. Interestingly, the total number of claims filed by plaintiffs does not increase significantly with the increased jurisdictional limit. We do find, however, changes to the composition of plaintiffs. Following the jurisdictional change, we find that plaintiffs using the small claims court are, on average, from richer neighborhoods. We also find that the proportion of plaintiffs from poorer neighborhoods drops. The drop‐off is most pronounced in plaintiffs from the poorest 10 percent of neighborhoods. We explore potential explanations for this regressive effect, including crowding out, congestion, increased legal representation, and behavioral influences. Our findings suggest that legislative attempts to make the courts more accessible may have unintended regressive consequences.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it