A linear model of fine enforcement with application to England and Wales

Fines are the most common sanction against criminal offenders in many countries. Economists have developed models for determining the optimal use of fines. Their models, however, generally abstract from problems of fine enforcement and assume that all fines are collected and that enforcement costs are zero. Criminologists and practitioners, on the other hand, have been very much aware of enforcement costs. Imprisonment for fine default is particularly costly and exacerbates the crowded prison conditions that exist in many countries. This paper extends previous economic models by dropping the limiting assumption of zero enforcement costs. The model is estimated using data from England and Wales and is used to evaluate alternative methods and levels of fine enforcement.     

Weight of authorship evidence with multiple categories of stylometric features: A multinomial-based discrete model

This study empirically demonstrates the efficacy of a two-level Dirichlet-multinomial statistical model (the Multinomial system) for computing likelihood ratios (LR) for linguistic, textual evidence with multiple stylometric feature types with discrete values. The LRs are calculated separately for each feature type, namely, word, character and part of speech N-grams (N = 1,2,3), which are combined as overall LRs through logistic regression fusion. The Multinomial system’s performance is compared with that of a previously proposed system with the cosine distance (the Cosine system) using the same data (i.e., documents collated from 2160 authors). The experimental results show that: (1) the Multinomial system outperforms the Cosine system with the fused feature types by a log-LR cost of ca. 0.01 ～ 0.05 bits; and (2) the Multinomial system is more advantageous in performance with longer documents than the Cosine system. Although the Cosine system is more robust overall against the sampling variability arising from the number of authors included in the reference and calibration databases, the Multinomial system can achieve reasonable stability in performance; for example, the standard deviation value of the log-LR cost becomes lower than 0.01 (10 random samplings of authors for the reference and calibration databases) with 60 or more authors in each database.