scholarly journals The Injustice of Opportunity: Clarence DeWitt Thorpe, Articulation, and the Inter-Institutional Ecology of Writing Assessment

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Andrew Moos
Author(s):  
Yeongmi Choi ◽  
Sumi Kim ◽  
So hyeon Lee ◽  
Youngmin Park

Author(s):  
Gordon L. Clark ◽  
Ashby H. B. Monk ◽  
Gordon L. Clark ◽  
Ashby H. B. Monk

In Chapter 7, the focus shifts to public agents and the process of contracting financial services and local pension funds in the US states. The costs of governing and managing this sector are addressed and an idealized model of the institutional design, administration, and supervision of the investment management process is introduced, laying out the forms and functions of pensions in relation to their beneficial purpose. In a brief overview of the US state and local PERS sector, its economic significance and distinctive institutional ecology are noted. The authors’ research demonstrates the extent to which the market for financial services in the US public pension-fund sector is Balkanized, implying significant transaction costs for both the buy and sell sides of the market, more often found at the city or metropolitan level than among funds within states or between funds of adjacent states.


2005 ◽  
Vol 33 (1) ◽  
pp. 101-113 ◽  
Author(s):  
P. Adam Kelly

Powers, Burstein, Chodorow, Fowles, and Kukich (2002) suggested that automated essay scoring (AES) may benefit from the use of “general” scoring models designed to score essays irrespective of the prompt for which an essay was written. They reasoned that such models may enhance score credibility by signifying that an AES system measures the same writing characteristics across all essays. They reported empirical evidence that general scoring models performed nearly as well in agreeing with human readers as did prompt-specific models, the “status quo” for most AES systems. In this study, general and prompt-specific models were again compared, but this time, general models performed as well as or better than prompt-specific models. Moreover, general models measured the same writing characteristics across all essays, while prompt-specific models measured writing characteristics idiosyncratic to the prompt. Further comparison of model performance across two different writing tasks and writing assessment programs bolstered the case for general models.


2020 ◽  
Vol 44 (3) ◽  
pp. 417-444 ◽  
Author(s):  
Eric B. Schneider

ABSTRACTBodenhorn et al. (2017) have sparked considerable controversy by arguing that the fall in adult stature observed in military samples in the United States and Britain during industrialization was a figment of selection on unobservables in the samples. While subsequent papers have questioned the extent of the bias (Komlos and A’Hearn 2019; Zimran 2019), there is renewed concern about selection bias in historical anthropometric datasets. Therefore, this article extends Bodenhorn et al.’s discussion of selection bias on unobservables to sources of children’s growth, specifically focusing on biases that could distort the age pattern of growth. Understanding how the growth pattern of children has changed is important because these changes underpinned the secular increase in adult stature and are related to child stunting observed in developing countries today. However, there are significant sources of unobserved selection in historical datasets containing children’s and adolescents’ height and weight. This article highlights, among others, three common sources of bias: (1) positive selection of children into secondary school in the late nineteenth and early twentieth centuries; (2) distorted height by age profiles created by age thresholds for enlistment in the military; and (3) changing institutional ecology that determines to which institutions children are sent. Accounting for these biases adjusts the literature in two ways: evidence of a strong pubertal growth spurt in the nineteenth century is weaker than formerly acknowledged and some long-run analyses of changes in children’s growth are too biased to be informative, especially for Japan.


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