4,009 research outputs found
Opening the 'black box': what does observational research reveal about processes and practices of governing?
No full textDespite several decades of research on governance, very little is known about processes and practices of governing and, crucially, the links between governing and organisational performance. This has led to calls to penetrate the ‘black box’ of the boardroom by conducting research which draws on data gathered through direct observation. Such calls, however, have so far produced a rather sparse and inchoate literature which would benefit from review in order to give shape to the field and provide direction for future research. Here, we critically examine the findings of this research, in particular focusing on three emergent themes: (1) the extent to which empirical research supports the established theories in the field, particularly agency and stewardship theories; (2) what research says about ‘good’ and ‘effective’ governance and the relationship between them; and (3) the methodological and conceptual orientations which frame this research, in particular the claims made for ‘processual’ approaches. We conclude with an agenda for taking the field forward in order to extend knowledge and to contribute to theory around governing
Nancy Dingham Watson Correspondence
No full textEntries include a typed letter of correspondence from children\u27s author Nancy Dingham Watson on Aldren A. Watson, Illustration & Design, Putney, Vermont, stationery with a red-inked print image of a train, in reply to the Maine State Library concerning her recent book When is Tomorrow? dedicated to her father and illustrated by her husband, and visits to Vinalhaven, Maine, prompted (in part) by a seasonal allergy to ragweed, with typed correspondence from Aldren Watson discussing his father-in-law\u27s delight on reading the book, a typographical error, notice of new farm book What Does A Begin With?, and a typed letter from the Maine State Library on receipt of her book gift for the Maine Author Collection
Stress and family satisfaction in parents of children with facial port-wine stains
No full textA cross-sectional survey was employed to assess parenting stress, family satisfaction, and parental concerns and to determine predictors of stress in parents of children with port-wine stains (PWSs). The participants were 46 parents of 24 children receiving treatment with pulsed dye laser photocoagulation for facial PWS at an outpatient dermatology clinic based at a university medical center. Outcome measures used were self-report instruments assessing psychosocial adjustment (Parenting Stress Index, Family Satisfaction Scale, and Parental Concerns Questionnaire). As a group, parents scored in the average range on the stress and family satisfaction measures when compared with a normative sample; five parents (11%) scored in the clinical range for stress. Forty-nine percent of the variance in parenting stress was accounted for by four variables: the child's age (? = 0.34; p = 0.031), the parents' degree of family satisfaction (? = ?0.27; p = 0.077), the level of parental concern regarding the child's facial PWS (? = 0.45; p = 0.005), and the parents' satisfaction with staff communication (? = ?0.51; p = 0.002). The data suggest that while, as a group, parents of children with a facial PWS report to be in the average range for psychological stress, some do not fare as well as others. Factors associated with lower stress include younger children, more family cohesion and adaptation, fewer parental concerns, and greater satisfaction with parent-staff communication. The potential for the development of medical complications and psychological problems over time suggests the need for treatment of the PWS at an early age. Health care providers should be prepared to screen for clinical levels of distress and to refer parents for psychological intervention when needed
Targeting assistance to the poor using household survey data
No full textIt is important that limited government resources be channeled to the poor, but it is not always easy to identify the poor. Which households should be given tranfers when reliable information on incomes is difficult to obtain? The authors of this paper present a simple method for targeting when income is not observable but other characteristics that are correlated with income can be observed. Using survey data taken from Cote d'Ivoire, they predict incomes based on observable characteristics and distribute transfers on the basis of those predictions. It appears that significant reductions in poverty can be achieved using this method.Environmental Economics&Policies,Rural Poverty Reduction,Services&Transfers to Poor,Safety Nets and Transfers,Poverty Assessment
2004-2005 Brad Watson
No full textBrad Watson is the author of two collections of stories and two novels, The Heaven of Mercury, which was a finalist for the 2002 National Book Award, and Miss Jane, longlisted for the 2016 National Book Award. His fiction has been published in The New Yorker, Granta, Ecotone, Electric Literature, and the Idaho Review, among other publications. He teaches at the University of Wyoming, Laramie.https://egrove.olemiss.edu/grisham_res/1015/thumbnail.jp
Reflections on the Life and Times of Alan Watson
No full textThe author summarizes the career of Alan Watson, J.D. and University of Georgia Law School faculty member
Heterogeneous Treatment Effect with Trained Kernels of the Nadaraya-Watson Regression
No full textA new method for estimating the conditional average treatment effect is
proposed in the paper. It is called TNW-CATE (the Trainable Nadaraya-Watson
regression for CATE) and based on the assumption that the number of controls is
rather large whereas the number of treatments is small. TNW-CATE uses the
Nadaraya-Watson regression for predicting outcomes of patients from the control
and treatment groups. The main idea behind TNW-CATE is to train kernels of the
Nadaraya-Watson regression by using a weight sharing neural network of a
specific form. The network is trained on controls, and it replaces standard
kernels with a set of neural subnetworks with shared parameters such that every
subnetwork implements the trainable kernel, but the whole network implements
the Nadaraya-Watson estimator. The network memorizes how the feature vectors
are located in the feature space. The proposed approach is similar to the
transfer learning when domains of source and target data are similar, but tasks
are different. Various numerical simulation experiments illustrate TNW-CATE and
compare it with the well-known T-learner, S-learner and X-learner for several
types of the control and treatment outcome functions. The code of proposed
algorithms implementing TNW-CATE is available in
https://github.com/Stasychbr/TNW-CATE
Picturing Validity: autoethnography and the representation of self?
No full textIn considering issues of “representation” and “realism,” the visual is inevitably invoked, yet in the current Western episteme, the relationship between the visible and the readable constitutes an enduring problem in which the image is generally subordinate to the text. In this article, the author examines what would happen if the usual relationship between verbal and visual was overturned and images were used to analyze text. In doing this, the author draws on the concept of “reverse ekphrasis” in the creation of a “gallery of validity,” which constitutes an interpretive framework for her autoethnographic research. The author situates this work within an approach characterized as the baroque, arguing that this provides a useful metaphor for qualitative research in the current moment
Heterogeneous Treatment Effect with Trained Kernels of the Nadaraya–Watson Regression
No full textA new method for estimating the conditional average treatment effect is proposed in this paper. It is called TNW-CATE (the Trainable Nadaraya–Watson regression for CATE) and based on the assumption that the number of controls is rather large and the number of treatments is small. TNW-CATE uses the Nadaraya–Watson regression for predicting outcomes of patients from control and treatment groups. The main idea behind TNW-CATE is to train kernels of the Nadaraya–Watson regression by using a weight sharing neural network of a specific form. The network is trained on controls, and it replaces standard kernels with a set of neural subnetworks with shared parameters such that every subnetwork implements the trainable kernel, but the whole network implements the Nadaraya–Watson estimator. The network memorizes how the feature vectors are located in the feature space. The proposed approach is similar to transfer learning when domains of source and target data are similar, but the tasks are different. Various numerical simulation experiments illustrate TNW-CATE and compare it with the well-known T-learner, S-learner, and X-learner for several types of control and treatment outcome functions. The code of proposed algorithms implementing TNW-CATE is publicly available
Land lease statement from Watson Land Company to Torakichi Isono, July 1, 1938
No full textStatement reflects payment due for second half of the year 1938 in the amount of $275. The statement is generated by the Watson Land Company, however, the lease is originated from the Dominguez Estate Company
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