Having reasons and the factoring account

It’s natural to say that when it’s rational for me to φ, I have reasons to φ. That is, there are reasons for φ-ing, and moreover, I have some of them. Mark Schroeder calls this view The Factoring Account of the having reasons relation. He thinks The Factoring Account is false. In this paper, I defend The Factoring Account. Not only do I provide intuitive support for the view, but I also defend it against Schroeder’s criticisms. Moreover, I show that it helps us understand the requirements of substantive rationality, or what we are rationally required to do when responding to reasons.     

An empirical study of item-test regression

Certain questions about the shape of item-test regressions are answered on the basis of data obtained from 103,275 examinees. Ten of the regressions obtained are shown in illustrative plots.This work was supported in part by the College Entrance Examination Board.     

Self-promotion is not ingratiating

Pairs of subjects participated in two unstructured conversations spaced one week apart. In the second session, one subject of the pair was asked to participate either as an ingratiator or as a self-promoter. Naive target subjects clearly distinguished between presenters attempting to appear likable or competent. As verified by observer subjects, ingratiators used reactive verbal and nonverbal behaviors, whereas promoters used proactive behaviors. Preparation time did not produce differential behavioral tactics. The results are discussed in terms of the use of conversational resources to produce the attributions of likability and competence.     

Justifying Partiality

It’s an undeniable fact about our moral lives that we are partial towards certain people and projects. Despite this, it has traditionally been very hard to justify partiality. In this paper I defend a novel partialist theory. The context of the paper is the debate between three different views of how partiality is justified. According to the first view, partiality is justified by facts about our ground projects. According to the second view, partiality is justified by facts about our relationships with the things that we are partial towards. And according to the third view, partiality is justified by facts about the things that we are partial towards. I argue that all three views contain part of the truth. We can see this by adopting a more sophisticated view of the weight of reasons. Once we do this, it will be clear that both facts about individuals and facts about relationships play a role in explaining why we often have stronger reason to act well towards those things we are partial towards. Further, I argue, facts about projects help explain why facts about relationships play the role that they do in determining the strength of our reasons.     

An interval estimate for making statistical inferences about true scores

A numerical procedure is outlined for obtaining an interval estimate of the regression of true score on observed score. Only the frequency distribution of observed scores is needed for this. The procedure assumes that the conditional distribution of observed scores for fixed true score is binomial. The procedure is applied to several sets of test data.This research was sponsored in part by the Personnel and Training Research Programs, Psychological Sciences Division, Office of Naval Research, under Contract No. N00014-69-C-0017, Contract Authority Identification Number, NR No. 150-303, and Educational Testing Service. Reproduction in whole or in part is permitted for any purpose of the United States Government.     

Estimating true-score distributions in psychological testing (an empirical bayes estimation problem)

The following problem is considered: Given that the frequency distribution of the errors of measurement is known, determine or estimate the distribution of true scores from the distribution of observed scores for a group of examinees. Typically this problem does not have a unique solution. However, if the true-score distribution is smooth, then any two smooth solutions to the problem will differ little from each other. Methods for finding smooth solutions are developed a) for a population and b) for a sample of examinees. The results of a number of tryouts on actual test data are summarized.The writer wishes to thank Diana Lees and Virginia Lennon, who wrote the computer programs, carried out some of the mathematical derivations, and helped with other important aspects of the work. This work was supported in part by contract Nonr-2752(00) between the Office of Naval Research and Educational Testing Service. Reproduction, translation, use and disposal in whole or in part by or for the United States Government is permitted.     

Type A behavior pattern and goal setting under different conditions of choice

This study examined the effects of the Type A behavior pattern on performance, goal acceptance, goal commitment, and expectancy of success under goal-setting conditions. Participants were assigned to one of four groups, assigned goal/assigned strategy, assigned goal/self-set strategy, self-set goal/assigned strategy, or self-set goal/self-set strategy. Results suggested that Type A persons were more likely to accept a difficult goal and remain committed to that goal, and that they had a higher expectancy of success than their Type B counterparts regardless of goal/strategy condition. With respect to performance, participants in the assigned goal/assigned strategy condition outperformed all other groups. A three-way interaction indicated that Type A persons performed better in the self-set goal/self-set strategy than Type B individuals. Implications of the findings regarding Type A and goal setting are discussed.     

A theoretical distribution for mental test scores

The negative hypergeometric distribution of raw scores on mental tests is derived from certain assumptions relating to test theory. This result is checked empirically in a number of examples. Further derivations lead to the bivariate distribution of parallel tests which is also verified with actual data. The bivariate distribution of raw score and true score is also derived from a further assumption. This distribution is used to set confidence limits for true scores for persons with a given raw score.This work was supported in part by contract Nonr-2752(00) between the Office of Naval Research and Educational Testing Service. Reproduction in whole or in part for any purpose of the United States Government is permitted.