The foundations of the rule of law

Formal conceptions of the rule of law are popular among contemporary legal philosophers. Nonetheless, the coherence of accounts of the rule of law committed to these conceptions is sometimes fractured by elements harkening back to substantive conceptions of the rule of law. I suggest that this may be because at its origins the ideal of the rule of law was substantive through and through. I also argue that those origins are older than is generally supposed. Most authors tend to trace the ideas of the rule of law and natural law back to classical Greece, but I show that they are already recognisable and intertwined as far back as Homer. Because the founding moment of the tradition of western intellectual reflection on the rule of law placed concerns about substantive justice at the centre of the rule of law ideal, it may be hard for this ideal to entirely shrug off its substantive content. It may be undesirable, too, given the rhetorical power of appeals to the rule of law. The rule of law means something quite radical in Homer; this meaning may provide a source of normative inspiration for contemporary reflections about the rule of law.

Rensch's rule in large herbivorous mammals derived from metabolic scaling

Rensch’s rule, which states that the magnitude of sexual size dimorphism tends to increase with increasing body size, has evolved independently in three lineages of large herbivorous mammals: bovids (antelopes), cervids (deer), and macropodids (kangaroos). This pattern can be explained by a model that combines allometry,life-history theory, and energetics. The key features are thatfemale group size increases with increasing body size and that males have evolved under sexual selection to grow large enough to control these groups of females. The model predicts relationships among body size and female group size, male and female age at first breeding,death and growth rates, and energy allocation of males to produce body mass and weapons. Model predictions are well supported by data for these megaherbivores. The model suggests hypotheses for why some other sexually dimorphic taxa, such as primates and pinnipeds(seals and sea lions), do or do not conform to Rensh’s rule.

New strings for old : the role of similarity processing in an incidental learning task

This paper reports three experiments that examine the role of similarity processing in McGeorge and Burton's (1990) incidental learning task. In the experiments subjects performed a distractor task involving four-digit number strings, all of which conformed to a simple hidden rule. They were then given a forced-choice memory test in which they were presented with pairs of strings and were led to believe that one string of each pair had appeared in the prior learning phase. Although this was not the case, one string of each pair did conform to the hidden rule. Experiment 1 showed that, as in the McGeorge and Burton study, subjects were significantly more likely to select test strings that conformed to the hidden rule. However, additional analyses suggested that rather than having implicitly abstracted the rule, subjects may have been selecting strings that were in some way similar to those seen during the learning phase. Experiments 2 and 3 were designed to try to separate out effects due to similarity from those due to implicit rule abstraction. It was found that the results were more consistent with a similarity-based model than implicit rule abstraction per se.

Mixed Logit Model Performance and Distributional Assumptions: Preferences and GM foods

Using mixed logit models to analyse choice data is common but requires ex ante specification of the functional forms of preference distributions. We make the case for greater use of bounded functional forms and propose the use of the Marginal Likelihood, calculated using Bayesian techniques, as a single measure of model performance across non nested mixed logit specifications. Using this measure leads to very different rankings of model specifications compared to alternative rule of thumb measures. The approach is illustrated using data from a choice experiment regarding GM food types which provides insights regarding the recent WTO dispute between the EU and the US, Canada and Argentina and whether labelling and trade regimes should be based on the production process or product composition.

Comparisons of host mitochondrial, nuclear and endosymbiont bacterial genes reveal cryptic fig wasp species and the effects of Wolbachia on host mtDNA evolution and diversity

Background Figs and fig-pollinating wasp species usually display a highly specific one-to-one association. However, more and more studies have revealed that the "one-to-one" rule has been broken. Co-pollinators have been reported, but we do not yet know how they evolve. They may evolve from insect speciation induced or facilitated by Wolbachia which can manipulate host reproduction and induce reproductive isolation. In addition, Wolbachia can affect host mitochondrial DNA evolution, because of the linkage between Wolbachia and associated mitochondrial haplotypes, and thus confound host phylogeny based on mtDNA. Previous research has shown that fig wasps have the highest incidence of Wolbachia infection in all insect taxa, and Wolbachia may have great influence on fig wasp biology. Therefore, we look forward to understanding the influence of Wolbachia on mitochondrial DNA evolution and speciation in fig wasps. Results We surveyed 76 pollinator wasp specimens from nine Ficus microcarpa trees each growing at a different location in Hainan and Fujian Provinces, China. We found that all wasps were morphologically identified as Eupristina verticillata, but diverged into three clades with 4.22-5.28% mtDNA divergence and 2.29-20.72% nuclear gene divergence. We also found very strong concordance between E. verticillata clades and Wolbachia infection status, and the predicted effects of Wolbachia on both mtDNA diversity and evolution by decreasing mitochondrial haplotypes. Conclusions Our study reveals that the pollinating wasp E. verticillata on F. microcarpa has diverged into three cryptic species, and Wolbachia may have a role in this divergence. The results also indicate that Wolbachia strains infecting E. verticillata have likely resulted in selective sweeps on host mitochondrial DNA.

Computationally efficient induction of classification rules with the PMCRI and J-PMCRI frameworks

In order to gain knowledge from large databases, scalable data mining technologies are needed. Data are captured on a large scale and thus databases are increasing at a fast pace. This leads to the utilisation of parallel computing technologies in order to cope with large amounts of data. In the area of classification rule induction, parallelisation of classification rules has focused on the divide and conquer approach, also known as the Top Down Induction of Decision Trees (TDIDT). An alternative approach to classification rule induction is separate and conquer which has only recently been in the focus of parallelisation. This work introduces and evaluates empirically a framework for the parallel induction of classification rules, generated by members of the Prism family of algorithms. All members of the Prism family of algorithms follow the separate and conquer approach.

TRCM: a methodology for temporal analysis of evolving concepts in Twitter

The Twitter network has been labelled the most commonly used microblogging application around today. With about 500 million estimated registered users as of June, 2012, Twitter has become a credible medium of sentiment/opinion expression. It is also a notable medium for information dissemination; including breaking news on diverse issues since it was launched in 2007. Many organisations, individuals and even government bodies follow activities on the network in order to obtain knowledge on how their audience reacts to tweets that affect them. We can use postings on Twitter (known as tweets) to analyse patterns associated with events by detecting the dynamics of the tweets. A common way of labelling a tweet is by including a number of hashtags that describe its contents. Association Rule Mining can find the likelihood of co-occurrence of hashtags. In this paper, we propose the use of temporal Association Rule Mining to detect rule dynamics, and consequently dynamics of tweets. We coined our methodology Transaction-based Rule Change Mining (TRCM). A number of patterns are identifiable in these rule dynamics including, new rules, emerging rules, unexpected rules and ?dead' rules. Also the linkage between the different types of rule dynamics is investigated experimentally in this paper.

Small x resummations confronted with F2(x, Q2) data

It has been observed recently that a consistent LO BFKL gluon evolution leads to a steep growth of F2(x, Q2) for x → 0 almost independently of Q2. We show that current data from the DESY HERA collider are precise enough to finally rule out a pure BFKL behaviour in the accessible small x region. Several attempts have been made by other groups to treat the BFKL type small x resummations instead as additions to the conventional anomalous dimensions of the successful renormalization group “Altarelli-Parisi” equations. We demonstrate that all presently available F2 data, in particular at lower values of Q2, can not be described using the presently known NLO (two-loop consistent) small x resummations. Finally we comment on the common reason for the failure of these BFKL inspired methods which result, in general, in too steep >x-dependencies as x → 0.

J-measure based hybrid pruning for complexity reduction in classification rules

Prism is a modular classification rule generation method based on the ‘separate and conquer’ approach that is alternative to the rule induction approach using decision trees also known as ‘divide and conquer’. Prism often achieves a similar level of classification accuracy compared with decision trees, but tends to produce a more compact noise tolerant set of classification rules. As with other classification rule generation methods, a principle problem arising with Prism is that of overfitting due to over-specialised rules. In addition, over-specialised rules increase the associated computational complexity. These problems can be solved by pruning methods. For the Prism method, two pruning algorithms have been introduced recently for reducing overfitting of classification rules - J-pruning and Jmax-pruning. Both algorithms are based on the J-measure, an information theoretic means for quantifying the theoretical information content of a rule. Jmax-pruning attempts to exploit the J-measure to its full potential because J-pruning does not actually achieve this and may even lead to underfitting. A series of experiments have proved that Jmax-pruning may outperform J-pruning in reducing overfitting. However, Jmax-pruning is computationally relatively expensive and may also lead to underfitting. This paper reviews the Prism method and the two existing pruning algorithms above. It also proposes a novel pruning algorithm called Jmid-pruning. The latter is based on the J-measure and it reduces overfitting to a similar level as the other two algorithms but is better in avoiding underfitting and unnecessary computational effort. The authors conduct an experimental study on the performance of the Jmid-pruning algorithm in terms of classification accuracy and computational efficiency. The algorithm is also evaluated comparatively with the J-pruning and Jmax-pruning algorithms.

"To strive for economic and social justice": welfare, sexuality, and party politics in San Francisco in the 1960s

This article explores how liberal politicians like Phil Burton of San Francisco joined with welfare rights lobbyists and bureaucrats to embrace late twntieth-century notions of sexual equality through a broader reconception of economic equality brought about by the expansion of the California welfare state in the early 1960s.