Representativeness of Case Law Research:Comparing Research Methods for Case Law Research Using Rechtspraak.nl (Dutch case law database) and Court File Studies
Bibliographic record
Abstract
Voor een representatieve weergave van de rechtspraktijk is (empirisch-)juridisch onderzoek idealiter gebaseerd op de volledige informatie uit alle relevante zaken. De rechtswetenschappelijke methode van dossieronderzoek, waarbij volledige (rechtbank-)dossiers ingezien en geanalyseerd worden, komt redelijk dichtbij dit ideaal. De uitvoering van dossieronderzoek is echter intensief, tijdrovend en afhankelijk van expliciete toestemming van de betrokken instanties. Mede hierom wordt binnen de rechtswetenschap veelvuldig gebruik gemaakt van de methode van rechtspraakonderzoek, waarbij openbaar toegankelijke rechtspraak op rechtspraak.nl wordt geanalyseerd. De vraag is echter in hoeverre rechtspraakonderzoek op basis van deze gepubliceerde beslissingen representatief is voor de rechtspraktijk, en daarmee hoe werkelijkheid en weergave zich in deze context tot elkaar verhouden?
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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 | 0.621 | 0.879 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.009 |
| Bibliometrics | 0.021 | 0.016 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.014 | 0.017 |
| Open science | 0.006 | 0.015 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".