On the Measurement of Segregation

This paper develops a measure of segregation based on two premises: (1) a measure of segregation should disaggregate to the level of individuals, and (2) an individual is more segregated the more segregated are the agents with whom she interacts. Developing three desirable axioms that any segregation measure should satisfy, we prove that one and only one segregation index satisfies our three axioms, and the two aims mentioned above; which we coin the Spectral Segregation Index. We apply the index to two well-studied social phenomena: residential and school segregation. We calculate the extent of residential segregation across major US cities using data from the 2000 US Census. The correlation between the Spectral index and the commonly- used dissimilarity index is .42. Using detailed data on friendship networks, available in the National Longitudinal Study of Adolescent Health, we calculate the prevalence of within-school racial segregation. The results suggests that the percent of minority students within a school, commonly used as a substitute for a measure of in-school segregation, is a poor proxy for social interactions.segregation, networks, social interactions, school segregation, residential segregation

Parameter-free agglomerative hierarchical clustering to model learners' activity in online discussion forums

L'anàlisi de l'activitat dels estudiants en els fòrums de discussió online implica un problema de modelització altament depenent del context, el qual pot ser plantejat des d'aproximacions tant teòriques com empíriques. Quan aquest problema és abordat des de l'àmbit de la mineria de dades, l'enfocament més comunament adoptat és el de la classificació no supervisada (o clustering), donant lloc, d'aquesta manera, a un escenari de clustering en el qual el nombre real de clústers és a priori desconegut. Per tant, aquesta aproximació revela una qüestió subjacent, la qual no és sinó un dels problemes més coneguts del paradigma del clustering: l'estimació del nombre de clústers, habitualment seleccionat per l'usuari concorde a algun tipus de criteri subjectiu que pot comportar fàcilment l'aparició de biaixos indesitjats en els models obtinguts. Amb l'objectiu d'evitar qualsevol intervenció de l'usuari en l'etapa de clustering, dos nous criteris d'unió entre clústers són proposats en la present tesi, els quals, al seu torn, permeten la implementació d'un nou algorisme de clustering jeràrquic aglomeratiu lliure de paràmetres. Un complet conjunt d'experiments indica que el nou algorisme de clustering és capaç de proporcionar solucions de clustering òptimes enfront d'una gran varietat d'escenaris de clustering, sent capaç de bregar amb diferents classes de dades, així com de millorar el rendiment ofert pels algorismes de clustering més àmpliament emprats en la pràctica. Finalment, una estratègia d'anàlisi de dues etapes basada en el paradigma del clustering subespaial és proposada a fi d'abordar adequadament el problema de la modelització de la participació dels estudiants en les discussions asíncrones. Combinada amb el nou algorisme clustering, l'estratègia proposada demostra ser capaç de limitar la intervenció subjectiva de l'usuari a les etapes d'interpretació del procés d'anàlisi i de donar lloc a una completa modelització de l'activitat duta a terme pels estudiants en els fòrums de discussió online.El análisis de la actividad de los estudiantes en los foros de discusión online acarrea un problema de modelización altamente dependiente del contexto, el cual puede ser planteado desde aproximaciones tanto teóricas como empíricas. Cuando este problema es abordado desde el ámbito de la minería de datos, el enfoque más comúnmente adoptado es el de la clasificación no supervisada (o clustering), dando lugar, de este modo, a un escenario de clustering en el que el número real de clusters es a priori desconocido. Por tanto, esta aproximación revela una cuestión subyacente, la cual no es sino uno de los problemas más conocidos del paradigma del clustering: la estimación del número de clusters, habitualmente seleccionado por el usuario acorde a algún tipo de criterio subjetivo que puede conllevar fácilmente la aparición de sesgos indeseados en los modelos obtenidos. Con el objetivo de evitar cualquier intervención del usuario en la etapa de clustering, dos nuevos criterios de unión entre clusters son propuestos en la presente tesis, los cuales, a su vez, permiten la implementación de un nuevo algoritmo de clustering jerárquico aglomerativo libre de parámetros. Un completo conjunto de experimentos indica que el nuevo algoritmo de clustering es capaz de proporcionar soluciones de clustering óptimas frente a una gran variedad de escenarios de clustering, siendo capaz de lidiar con diferentes clases de datos, así como de mejorar el rendimiento ofrecido por los algoritmos de clustering más ampliamente utilizados en la práctica. Finalmente, una estrategia de análisis de dos etapas basada en el paradigma del clustering subespacial es propuesta a fin de abordar adecuadamente el problema de la modelización de la participación de los estudiantes en las discusiones asíncronas. Combinada con el nuevo algoritmo clustering, la estrategia propuesta demuestra ser capaz de limitar la intervención subjetiva del usuario a las etapas de interpretación del proceso de análisis y de dar lugar a una completa modelización de la actividad llevada a cabo por los estudiantes en los foros de discusión online.The analysis of learners' activity in online discussion forums leads to a highly context-dependent modelling problem, which can be posed from both theoretical and empirical approaches. When this problem is tackled from the data mining field, a clustering-based perspective is usually adopted, thus giving rise to a clustering scenario where the real number of clusters is a priori unknown. Hence, this approach reveals an underlying problem, which is one of the best-known issues of the clustering paradigm: the estimation of the number of clusters, habitually selected by user according to some kind of subjective criterion that may easily lead to the appearance of undesired biases in the obtained models. With the aim of avoiding any user intervention in the cluster analysis stage, two new cluster merging criteria are proposed in the present thesis, which allow to implement a novel parameter-free agglomerative hierarchical algorithm. A complete set of experiments indicate that the new clustering algorithm is able to provide optimal clustering solutions in the face of a great variety of clustering scenarios, both having the ability to deal with different kinds of data and outperforming clustering algorithms most widely used in practice. Finally, a two-stage analysis strategy based on the subspace clustering paradigm is proposed to properly tackle the issue of modelling learners' participation in the asynchronous discussions. In combination with the new clustering algorithm, the proposed strategy proves to be able to limit user's subjective intervention to the interpretation stages of the analysis process and to lead to a complete modelling of the activity performed by learners in online discussion forums

Revisiting the Dimensions of Residential Segregation

The first major work to analyze the dimensions of segregation, done in the late 1980s by Massey and Denton, found five dimensions which explained the phenomenon of segregation. Since the original work was done in 1988 it seems relevant to revisit the issue with new data. Massey and Denton used the technique of factor analysis to identify the latent structure underlying the phenomenon. In this research their methodology is applied to a more complete data set from the 1980 Census to confirm their results and extend the methodology. Due to problems identified during the analysis confirmation was not possible. However, a simpler structure was identified which is comprised of only two factors. This structure is replicated when the methodology is applied to the 1990 and 2000 Census data thereby proving the robustness of the methodology

Oleogustus: The Unique Taste of Fat

Considerable mechanistic data indicate there may be a sixth basic taste: fat. However, evidence demonstrating that the sensation of non-esterified fatty acids (the proposed stimuli for “fat taste”) differs qualitatively from other tastes is lacking. Using perceptual mapping, we demonstrate that medium and long-chain non-esterified fatty acids have a taste sensation that is distinct from other basic tastes (sweet, sour, salty, and bitter). While some overlap was observed between these NEFA and umami taste, this overlap is likely due to unfamiliarity with umami sensations rather than true similarity. Shorter chain fatty acids stimulate a sensation similar to sour, but as chain length increases this sensation changes. Fat taste oral signaling, and the different signals caused by different alkyl chain lengths, may hold implications for food product development, clinical practice, and public health policy

Habitat relationships and gene flow of Martes americana in northern Idaho

Forest fragmentation can have a dramatic effect on landscape connectivity and dispersal of animals, potentially reducing gene flow within and among populations. American marten populations (Martes americana) are sensitive to forest fragmentation and the spatial configuration of patches of remnant mature forest has an important impact on habitat quality. This study represents an extensive multiple scale habitat relationships analysis conducted for American marten. In conjunction with Idaho Department of Fish and Game (IDFG) and the U.S. Forest Service, genetic data on marten populations across the Idaho Panhandle National Forest was used to build habitat relationships models. Over 3 years of winter fieldwork during 2004, 2005, and 2006, I detected martens at 569 individual hair snare stations distributed across a 3,000 square kilometer study area covering the Selkirk, Purcell, and Cabinet Mountain ranges. I investigated habitat relationships of this population of Martes americana in the Idaho Panhandle National Forest (IPNF) at three spatial scales: Plot, Home Range, and Multiple-Scale. I used bivariate scaling to measure each environmental variable across a broad range of radii ranging from 90m-1080m around each sample station. I used an information-theoretic approach to rank 45 a priori candidate models that described hypothesized habitat relationships at each spatial scale. At the plot scale, marten presence was positively predicted by the Percentage of Landscape (PLand) comprised of large sawtimber, and negatively predicted by PLand of seedling/sapling timber type. At the home range scale, the probability of detecting a marten decreased with increasing amounts of fragmentation and highly contrasted edges between patches of large sawtimber and patches of seedling/sapling and non-stocked patches. In the multiple-scale analysis, I used a variable screening step to find variables that were universal and consistent throughout all models in order to build candidate models. PLand comprised of large homogeneous patches of large sawtimber was a positive predictor of marten presence, while highly contrasted edges and fragmentation were strong negative predictors of marten presence. The scale at which martens selected habitats varied greatly across variables. Martens actively selected for high quality habitat at the fine scale (plot level) and strongly avoided areas comprised of seedling/sapling and non-stocked timber areas. Martens negatively responded to high contrast edges and strongly avoided them. Juxtaposition and configuration of patches of large sawtimber was important to marten habitat selection. This study demonstrates the importance of investigating marten habitat at multiple spatial scales and provides insights to linkages among scales and how martens respond to forest fragmentation. Genetic information was used to model genetic relationships of this marten population with respect to environmental and spatial variables within my study landscape. Over three field seasons 70 individual marten were detected across the study area. The genetic similarities were based on the pair-wise percentage dissimilarity among all individuals based on 7 microsatellite loci. I compared their genetic similarities with several landscape resistance hypotheses. The landscape resistance hypotheses describe a range of potential relationships between movement cost and landcover, elevation, roads, Euclidean distance and valleys between mountain ranges as barriers. The degree of support for each model was tested with causal modeling on resemblance matrices using partial Mantel tests. Hypotheses of Isolation by Distance and Isolation by Barrier were not supported, and Isolation by Landscape Resistance proved to be the best model describing genetic patterns of Martes americana in the IPNF. Elevation 1600m with a standard deviation of 600m was the most highly supported landscape resistance model correlated to genetic structure of marten in this landscape. Correlating genetic similarity of individuals across large landscapes with hypothetical movement cost models can give reliable inferences about population connectivity. By linking cost modeling to the actual patterns of genetic similarity among individuals it is possible to obtain rigorous, empirical models describing the relationship between landscape structure and gene flow, and to produce speciesspecific maps of landscape connectivity, and can provide managers with critical information to better administer our forests for meso-carnivores and other species of concern

Atoll research bulletin.

no.531-542 (2005