7,298 research outputs found
What’s the Harm in Climate Change?
A popular argument against direct duties for individuals to address climate change holds that only states and other powerful collective agents must act. It excuses individual actions as harmless since they (1) are neither necessary nor sufficient to cause harm, (2) arise through normal activity, and (3) have no clear victims. Philosophers have challenged one or more of these assumptions; however, I show that this definition of harm also excuses states and other collective agents. I cite two examples of this in public discourse and suggest we reconsider the notion of harmful action in our discussions about climate change
Sharing Responsibility for Divesting from Fossil Fuels
Governments have been slow to address climate change. If non-governmental agents share a responsibility in light of the slow pace of government action then it is a collective responsibility. I examine three models of collective responsibility, especially Iris Young\u27s social connection model, and assess their value for identifying a collective, among all emitters, that can share responsibility. These models can help us better understand both the growth of the movement to divest from fossil fuels and the nature of responsibility for collective action problems. Universities and colleges share a responsibility because they occupy similar positions of, among other things, power and privilege
Going Fossil Free: A Lesson in Climate Activism and Collective Responsibility
Colleges and universities already contribute significantly to the fight against climate change, but the UN has recently called upon them to do even more. The purpose of this article is to demonstrate that institutions of higher education play a unique role in combating climate change and other structural injustices, not only by conducting research and disseminating knowledge, but also by fostering a form of collective political responsibility. A philosophical analysis of different forms of collective responsibility, with specific attention to the Fossil Free divestment movement, reveals how social position facilitates this contribution more so in colleges than in other institutions
Reconceiving Responsibility: A review of Iris Marion Young’s Responsibility for Justice
In Responsibility for Justice, published 5 years after her untimely death, Iris Marion Young addresses the difficulties of thinking about responsibility in our complex, globally interconnected world. Our everyday errands, such as shopping for food, clothing and even light bulbs, now raise questions about our connection to grave injustices that occur around the world. Yet the limits of our ability to think seriously about these connections are evident. Even tracking responsibility within localized events is difficult when multiple layers of agency are involved. For instance, is BP, Transocean, or Halliburton responsible for the Deepwater debacle? 1 Unfortunately, Young began working on these questions–so pressing in our time–just a few years before she passed away. Yet the fruits of her labors are promising. Her recent book is a serious development of her social connection model of responsibility, a
Patterns of anxiety symptoms in toddlers and preschool-age children: Evidence of early differentiation
The degree to which young children’s anxiety symptoms differentiate according to diagnostic groupings is under-studied, especially in children below the age of 4 years. Theoretical (confirmatory factor analysis, CFA) and statistical (exploratory factor analysis, EFA) analytical methods were employed to test the hypothesis that anxiety symptoms among 2–3-year-old children from a non-clinical, representative sample would differentiate in a manner consistent with current diagnostic nosology. Anxiety symptom items were selected from two norm-referenced parent-report scales of child behavior. CFA and EFA results suggested that anxiety symptoms aggregate in a manner consistent with generalized anxiety, obsessive–compulsive symptoms, separation anxiety, and social phobia. Multi-dimensional models achieved good model fit and fit the data significantly better than undifferentiated models. Results from EFA and CFA methods were predominantly consistent and supported the grouping of early childhood anxiety symptoms into differentiated, diagnostic-specific categories
''Sepan que la tiranÃa de arriba, enjendra la rebelión de abajo''. Represión contra los anarquistas: la historia de Voltaire Argandoña y Hortensia Quinio (Santiago, 1913).
Model-Based Edge Detector for Spectral Imagery Using Sparse Spatiospectral Masks
Two model-based algorithms for edge detection in spectral imagery are developed that specifically target capturing intrinsic features such as isoluminant edges that are characterized by a jump in color but not in intensity. Given prior knowledge of the classes of reflectance or emittance spectra associated with candidate objects in a scene, a small set of spectral-band ratios, which most profoundly identify the edge between each pair of materials, are selected to define a edge signature. The bands that form the edge signature are fed into a spatial mask, producing a sparse joint spatiospectral nonlinear operator. The first algorithm achieves edge detection for every material pair by matching the response of the operator at every pixel with the edge signature for the pair of materials. The second algorithm is a classifier-enhanced extension of the first algorithm that adaptively accentuates distinctive features before applying the spatiospectral operator. Both algorithms are extensively verified using spectral imagery from the airborne hyperspectral imager and from a dots-in-a-well midinfrared imager. In both cases, the multicolor gradient (MCG) and the hyperspectral/spatial detection of edges (HySPADE) edge detectors are used as a benchmark for comparison. The results demonstrate that the proposed algorithms outperform the MCG and HySPADE edge detectors in accuracy, especially when isoluminant edges are present. By requiring only a few bands as input to the spatiospectral operator, the algorithms enable significant levels of data compression in band selection. In the presented examples, the required operations per pixel are reduced by a factor of 71 with respect to those required by the MCG edge detector
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