Exploring Reciprocity in International Service Learning Programs

Using aspects of grounded theory methodology, this study explored the perceptions and practical implementation of reciprocity in International Service Learning (ISL) Programs. Data were collected through interviews with nine ISL practitioners representing a variety of organizations offering international service learning programs. Findings suggest that multiple conceptualizations of ISL programs exist. ISL programs are interdisciplinary in nature and that using reciprocity as a guiding framework is problematic. Further attention is needed in relation to shifting the guiding framework of ISL programs from reciprocity to interdependence.

On blame-freeness and reciprocity: an experimental study

The theory of reciprocity is predicated on the assumption that people are willing to reward nice or kind acts and to punish unkind ones. This assumption raises the question as to how to define kindness. In this paper we offer a new definition of kindness that we call “blame-freeness.” Put most simply, blame-freeness states that in judging whether player i has been kind or unkind to player j in a social situation, player j would have to put himself in the strategic position of player i, while retaining his preferences, and ask if he would have acted in a manner that was worse than i did under identical circumstances. If j would have acted in a more unkind manner than i acted, then we say that j does not blame i for his behavior. If, however, j would have been nicer than i was, then we say that “j blames i” for his actions (i’s actions were blameworthy). We consider this notion a natural, intuitive and empirically relevant way to explain the motives of people engaged in reciprocal behavior. After developing the conceptual framework, we then test this concept in a laboratory experiment involving tournaments and find significant support for the theory.

Gauss : la revolución de las matemáticas del siglo XIX.

Reflexión sobre la figura de Carl Fiedrich Gauss y la importancia que tuvo en las matemáticas del siglo XIX. A partir de su conocido teorema se recorren los campos en que el matemático tuvo ciertas aportaciones.

Intention-based economic theories of reciprocity

In recent years, several experiments have shown individuals exhibit authentic reciprocal behaviour in anonymous one-shot interactions. As reciprocity has been shown to be relevant in several economic fields, there have also been several attempts to model reciprocal bahaviour. I review the intention-based models of reciprocity and present an example of teacher management in the public sector in which the government offers an incentive scheme to implement a program. The incentive scheme has a prisoner´s dilemma structure. In both simultaneous and sequential games, equilibrium results may differ from those predicted by standard theory.

Gauss y Goya : los dos gigantes que se acercaron a las cosas.

Recorrido por parte de la obra del físico Gauss y del pintor Goya. Se trata de establecer puntos comunes entre las diferentes obras de ambos, tanto en el enfoque como en la visión de cada uno de ellos.

Gauss y el polígono regular de 17 lados.

Se recoge uno de los concepto más destacados de Carl Friedrich Gauss como es el polígono regular de 17 lados. Se estudian los diferentes pasos que llevan a la construcción de este polígono con los diferentes cálculos aritméticos.

Dificultades asociadas con la resolución por parte de estudiantes de segundo curso de bachillerato de un problema relacionado con la Ley de Gauss.

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Los applets de funciones en el Proyecto Gauss.

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Gauss : recursos interactivos de Matemáticas : Primaria y ESO.

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Approximate Gauss-Newton methods for nonlinear least squares problems

The Gauss–Newton algorithm is an iterative method regularly used for solving nonlinear least squares problems. It is particularly well suited to the treatment of very large scale variational data assimilation problems that arise in atmosphere and ocean forecasting. The procedure consists of a sequence of linear least squares approximations to the nonlinear problem, each of which is solved by an “inner” direct or iterative process. In comparison with Newton’s method and its variants, the algorithm is attractive because it does not require the evaluation of second-order derivatives in the Hessian of the objective function. In practice the exact Gauss–Newton method is too expensive to apply operationally in meteorological forecasting, and various approximations are made in order to reduce computational costs and to solve the problems in real time. Here we investigate the effects on the convergence of the Gauss–Newton method of two types of approximation used commonly in data assimilation. First, we examine “truncated” Gauss–Newton methods where the inner linear least squares problem is not solved exactly, and second, we examine “perturbed” Gauss–Newton methods where the true linearized inner problem is approximated by a simplified, or perturbed, linear least squares problem. We give conditions ensuring that the truncated and perturbed Gauss–Newton methods converge and also derive rates of convergence for the iterations. The results are illustrated by a simple numerical example. A practical application to the problem of data assimilation in a typical meteorological system is presented.