904 resultados para opportunity


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Given a graph G and a set X ⊆ V(G), the relative Wiener index of X in G is defined as WX (G) = {u,v}∈X 2  dG(u, v) . The graphs G (of even order) in which for every partition V(G) = V1 +V2 of the vertex set V(G) such that |V1| = |V2| we haveWV1 (G) = WV2 (G) are called equal opportunity graphs. In this note we prove that a graph G of even order is an equal opportunity graph if and only if it is a distance-balanced graph. The latter graphs are known by several characteristic properties, for instance, they are precisely the graphs G in which all vertices u ∈ V(G) have the same total distance DG(u) = v∈V(G) dG(u, v). Some related problems are posed along the way, and the so-called Wiener game is introduced.

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Presentation for Research Skills

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La medición de la desigualdad de oportunidades con las bases de PISA implican varias limitaciones: (i) la muestra sólo representa una fracción limitada de las cohortes de jóvenes de 15 años en los países en desarrollo y (ii) estas fracciones no son uniformes entre países ni entre periodos. Lo anterior genera dudas sobre la confiabilidad de estas mediciones cuando se usan para comparaciones internacionales: mayor equidad puede ser resultado de una muestra más restringida y más homogénea. A diferencia de enfoques previos basados en reconstrucción de las muestras, el enfoque del documento consiste en proveer un índice bidimensional que incluye logro y acceso como dimensiones del índice. Se utilizan varios métodos de agregación y se observan cambios considerables en los rankings de (in) equidad de oportunidades cuando solo se observa el logro y cuando se observan ambas dimensiones en las pruebas de PISA 2006/2009. Finalmente se propone una generalización del enfoque permitiendo otras dimensiones adicionales y otros pesos utilizados en la agregación.

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We assess inequality of opportunity in educational achievement in six Latin American countries, employing two waves of PISA data (2006 and 2009). By means of a non-parametric approach using a decomposable inequality index, GE(0), we rank countries according to their degree of inequality of opportunity. We work with alternative characterizations of types: school type (public or private), gender, parental education, and combinations of those variables. We calculate incremental contributions of each set of circumstances to inequality. We provide rankings of countries based on unconditional inequalities (using conventional indices) and on conditional inequalities (EOp indices), and the two sets of rankings do not always coincide. Inequality of opportunities range from less than 1% to up to 27%, with substantial heterogeneity according to the year, the country, the subject and the specificication of circumstances. Robustness checks based on bootstrap and the use of an alternative index confirm most of the initial results.

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Routine milk recording data, often covering many years, are available for approximately half the dairy herds of England and Wales. In addition to milk yield and quality, these data include production events that can be used to derive objective Key Performance Indicators (KPI) describing a herd's fertility and production. Recent developments in information systems give veterinarians and other technical advisers access to these KPIs on-line. In addition to reviewing individual herd performance, advisers can establish local benchmark groups to demonstrate the relative performance of similar herds in the vicinity. The use of existing milk recording data places no additional demands on farmer's time or resources. These developments could also readily be exploited by universities to introduce veterinary undergraduates to the realities of commercial dairy production.

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This paper investigates the extent to which clients were able to influence performance measurement appraisals during the downturn in commercial property markets that began in the UK during the second half of 2007. The sharp change in market sentiment produced speculation that different client categories were attempting to influence their appraisers in different ways. In particular, it was recognised that the requirement for open‐ended funds to meet redemptions gave them strong incentives to ensure that their asset values were marked down to market. Using data supplied by Investment Property Databank, we demonstrate that, indeed, unlisted open‐ended funds experienced sharper drops in capital values than other fund types in the last quarter of 2007, after the market turning point and at the time when redemptions were at their highest. These differences are statistically significant and cannot simply be explained by differences in portfolio composition. Client influence on appraisal forms one possible explanation of the results observed: the different pressures on fund managers resulting in different appraisal outcomes.