14‐month‐olds exploit verbs’ syntactic contexts to build expectations about novel words

During their second year of life, infants develop a rudimentary understanding of grammatical categories based on their knowledge and use of frequent function words. The current study inquired whether, at only 14 months of age, infants can track co‐occurrence patterns between function words and content words (e.g., determiners can precede nouns, and pronouns can precede verbs), and use these previously encountered syntactic contexts to build expectations about which function words can co‐occur with novel words. Using a habituation paradigm, French‐learning 14‐month‐olds were presented with utterances containing two novel words preceded by function words (either two determiners in the Novel Nouns condition or two pronouns in the Novel Verbs conditions). We found that at test, infants looked longer during trials in which the novel words occurred in an unexpected syntactic context (following a pronoun for infants in the Novel Nouns condition and following a determiner for infants in the pooled analysis of the three Novel Verbs conditions). Hence, our results confirm previous findings on infants’ sensitivity to noun contexts and most importantly demonstrate that their sensitivity to the co‐occurrence of verbs with pronouns begins much earlier than previously understood.     

The Probabilistic Final Standing Calculator: a fair stochastic tool to handle abruptly stopped football seasons

AStA Advances in Statistical Analysis - The COVID-19 pandemic has left its marks in the sports world, forcing the full stop of all sports-related activities in the first half of 2020. Football...     

Charting and theorising the territorialisation of agricultural policy

Against a background of contestation of European agricultural policy, the territorial dimension is one of the prominent factors in proposals for shaping new rules of public action. This situation has been brought about by shifts in the nature of the challenges facing farming and in society's expectations of it, but also by a change in the forms that public policy may take, which is challenging the hegemony of the nation states in matters of economic and social organisation. We attempt to characterise this territorialisation of public policy in agriculture from a regulationist standpoint and on the basis of research conducted in France. This involves three points: the renewal of decision-making procedures, the adaptation of public action to local specificities and the offsetting of market effects. Empirical findings show that these three factors are only marginal aspects of the changes that have come about in public action in farming: the territorial dimension is not at present the vector of any far-reaching change to the underlying principles and ground rules in this domain. However, these three emerging rationales do give a preview of new forms of regulation in the farming sector.     

Using Task Clarification and Feedback Training to Improve Staff Performance in an East African Nongovernmental Organization

The present study used a multiple-baseline design to illustrate the effectiveness of an intervention package consisting of a multipurpose job aid and feedback training in improving the performance of supervisors and animal trainers in a nongovernmental organization headquartered in East Africa. Prior to the intervention, the performance of three supervisors and three animal trainers was suboptimal. Performance improved when supervisors were taught to use the job aid and provide feedback, and reached a high and consistent level during a subsequent phase, in which supervisors used the job aid independently. Limited maintenance and generalization data suggest that the intervention package produced lasting and generalized effects, and social validity data suggest that supervisors viewed the intervention as acceptable. These findings appear to be the first experimentally controlled demonstration of the potential value of organizational behavior management in improving performance in nongovernmental organizations working in resource-poor areas.     

Prevalence rate of DSM mental disorders among adolescents living in residential group homes of the French Child Welfare System

Purpose

To determine the prevalence of some major mental disorders among adolescents living in a residential group home and the distribution of these disorders by gender.

Method

The participants included 183 adolescents (13–17 years old) living in residential group homes of the Child Welfare System in the county of Bouches-du-Rhône (South of France). A structured psychiatric Diagnostic Interview Schedule for Children was used to assess the existence of Anxiety Disorder (AD), Major Depression (MD), Conduct Disorder (CD), Eating Disorder (ED), Enuresia (En), Psychosis Screen (PS) and Attention Deficit Hyperactivity Disorder (ADHD) among the study participants over the six-month period before the assessment was taken. The existence of Suicide Attempts (SA) during the lifetime of each child was also assessed.

Results

Of the youths qualified, 48.6% as having at least one psychiatric disorder during the last six months (AD: 28.4%; CD: 15.3%; MD: 14.8%; PS: 18.6%; ADHD: 3.8%), and SA have been reported in 23% of them. Females were more affected than boys (p < 0.001) with 64.9% having at least one disorder compared to 36.8% of boys; AD: 49.3% vs. 13.2%; and MD: 27.3% vs. 5.6%.

Conclusion

Adolescents living in residential group homes of the Child Welfare System in France have notably high rates of mental disorder (about three times more than those of the general population of the same age), similar to the patterns found in adolescents in North America and Europe. These data are the first of their kind in France and will guide necessary changes to the child welfare system.     

PRM inference using Jaffray &; Faÿ’s Local Conditioning

Probabilistic Relational Models (PRMs) are a framework for compactly representing uncertainties (actually probabilities). They result from the combination of Bayesian Networks (BNs), Object-Oriented languages, and relational models. They are specifically designed for their efficient construction, maintenance and exploitation for very large scale problems, where BNs are known to perform poorly. Actually, in large-scale problems, it is often the case that BNs result from the combination of patterns (small BN fragments) repeated many times. PRMs exploit this feature by defining these patterns only once (the so-called PRM’s classes) and using them through multiple instances, as prescribed by the Object-Oriented paradigm. This design induces low construction and maintenance costs. In addition, by exploiting the classes’ structures, PRM’s state-of-the-art inference algorithm “Structured Variable Elimination” (SVE) significantly outperforms BN’s classical inference algorithms (e.g., Variable Elimination, VE; Local Conditioning, LC). SVE is actually an extension of VE that simply exploits classes to avoid redundant computations. In this article, we show that SVE can be enhanced using LC. Although LC is often thought as being outperformed by VE-like algorithms in BNs, we do think that it should play an important role for PRMs because its features are very well suited for best exploiting PRM classes. In this article, relying on Faÿ and Jaffray’s works, we show how LC can be used in conjunction with VE and deduce an extension of SVE that outperforms it for large-scale problems. Numerical experiments highlight the practical efficiency of our algorithm.     

Morphological differences along a chronological gradient of urbanisation in an endemic insectivorous bird of New Zealand

Urbanisation constitutes one of the most rapid human-induced environmental changes, developing at the expense of natural and semi-natural habitats. It often implies alterations of many abiotic and biotic factors and contributes to create new environmental conditions, including temperature, food resources, competition and predation. Despite increasing empirical evidence of intra-specific divergence in phenotypic traits (e.g., physiological, behavioural or morphological) between urban and rural individuals, such patterns have often remained disconnected from the underlying mechanisms involved. In the current study, we tested for divergence in functional morphological traits that are related to feeding ecology (i.e., bill morphology, body mass and condition) and/or to the locomotory performance in escaping from predators (i.e., wing, tarsus and tail morphology, body mass and condition) along a chronological gradient of urbanisation (old urban, recent urban and rural areas), using the New Zealand fantail, an endemic insectivorous passerine species. We found divergences in phenotypic traits related to bill morphology along the urban–rural gradient: birds inhabiting the old urban area had stubbier bills (i.e., shorter, deeper and wider bills) than those inhabiting the recent urban and rural areas. We did not detect any difference in locomotion-related morphological traits. Our results suggest the urbanisation-induced alteration in food resources may drive morphological divergence in bird populations. We emphasized the need for mechanistic and experimental studies, with a particular focus on resource-based mechanisms, to identify more precisely the morphological responses of urban populations to changes in food composition, and the resulting implications for communities in urban ecosystems.

     

Model-based clustering of multivariate ordinal data relying on a stochastic binary search algorithm

We design a probability distribution for ordinal data by modeling the process generating data, which is assumed to rely only on order comparisons between categories. Contrariwise, most competitors often either forget the order information or add a non-existent distance information. The data generating process is assumed, from optimality arguments, to be a stochastic binary search algorithm in a sorted table. The resulting distribution is natively governed by two meaningful parameters (position and precision) and has very appealing properties: decrease around the mode, shape tuning from uniformity to a Dirac, identifiability. Moreover, it is easily estimated by an EM algorithm since the path in the stochastic binary search algorithm can be considered as missing values. Using then the classical latent class assumption, the previous univariate ordinal model is straightforwardly extended to model-based clustering for multivariate ordinal data. Parameters of this mixture model are estimated by an AECM algorithm. Both simulated and real data sets illustrate the great potential of this model by its ability to parsimoniously identify particularly relevant clusters which were unsuspected by some traditional competitors.     

Son preference, sex selection, and kinship in Vietnam

This article examines the recent rise in the sex ratio at birth in Vietnam and relates its emergence to kinship systems and ethnic composition using 2009 census micro-data. Presentation of the main socioeconomic and ethnic differentials in birth masculinity is followed by a review of the three intermediate factors leading to increases in the sex ratio at birth: prenatal technology, declining fertility, and gender bias. An indirect measurement of fertility behavior is used to demonstrate the close association between levels of the sex ratio at birth and the intensity of son preference. Data on household composition indicate that Vietnam is characterized by the co-existence of kinship patterns typical of East and Southeast Asia. Son preference in Vietnam is found to be related to the prevalence of more traditional patrilineal systems. The article concludes by considering the implications of the cultural dimensions of prenatal sex selection for policy responses and for the likely future change in the sex ratio at birth.