Forgiveness in The Arab and Islamic Contexts

This essay explores the current and historical meaning of forgiveness in Arab and Islamic cultural and religious contexts. It also hopes to encourage further empirical research on this understudied topic in both religious and peacebuilding studies. In addition to the perceived meaning of forgiveness in an Arab Islamic context, this essay examines the links between forgiveness and reconciliation. Relying on religious sources including the Qur'an and Hadith, as well as certain events in Islamic history, the essay identifies various ways to conceptualize and explain the meaning of forgiveness. This theoretical and conceptual segment is followed by a section which explores current perceptions of forgiveness among Arab Muslim teachers in five different communities. The empirical data for this analysis is based on a larger comparative regional study that has been completed through surveys and structured interviews with educators from Lebanon, Jordan, Egypt, and Palestinians from the West Bank and Israel. Our study concluded that the teachers' perceptions of forgiveness were mainly derived from religious sources and identities and that Islamic religious discourse provided a solid foundation for framing the meaning of forgiveness.     

Data‐driven approaches to information access

This paper summarizes three lines of research that are motivated by the practical problem of helping users find information from external data sources, most notably computers. The application areas include information retrieval, text categorization, and question answering. A common theme in these applications is that practical information access problems can be solved by analyzing the statistical properties of words in large volumes of real world texts. The same statistical properties constrain human performance, thus we believe that solutions to practical information access problems can shed light on human knowledge representation and reasoning.     

Trait tendencies to forgive,punish, and exonerate oneself: A multi-study investigation

In two studies (N’s = 515 and 359), we examine the utility of the Dual-Process Model of Self-Forgiveness for conceptualizing and measuring trait self-forgiveness with South African and American adults. Exploratory and confirmatory factor analyses of the trait-adapted Dual-Process Self-Forgiveness Scale supported an eight-item, two-factor structure of self-forgivingness consistent with prior theorizing and empirical evidence. The trait-adapted measure predicted incrementally more variance in outcomes beyond an existing measure of trait self-forgiveness. Latent subgroups characterized by tendencies to forgive, punish, and exonerate oneself in response to wrongdoing or failure were identified. Comparisons of mean differences provided preliminary evidence supporting the validity of the subgroups. Implications of the findings for conceptualizing and measuring self-forgiveness are discussed.     

Rare Constructions Are More Often Sentence‐Initial

Main clause phenomena (MCPs) are syntactic constructions that occur predominantly or exclusively in main clauses. I propose a processing explanation for MCPs. Sentence processing is easiest at the beginning of the sentence (requiring less search); this follows naturally from widely held assumptions about sentence processing. Because of this, a wider variety of constructions can be allowed at the beginning of the sentence without overwhelming the sentence‐processing mechanism. Unlike pragmatic and grammatical accounts of MCPs, the processing account predicts avoidance of MCPs in non‐initial main clauses (non‐initial coordinate clauses and premodified clauses). A corpus study supports these predictions, but it is somewhat inconclusive. A further corpus study examines another type of syntactic construction, premodifying adjunct phrases (“openers”); the prediction here is that less common types of opener will be especially avoided in non‐initial contexts. The prediction is confirmed, supporting the processing view of rare constructions.     

My Country,Right or Wrong: Education,Accumulated Democratic Experience,and Political Socialization of Blind Patriotism

Although educational attainment has been identified as a significant factor that reduces uncritical positive attachment to one's country (i.e., blind patriotism), little is known about whether the remedial effect of education on uncritical patriotism is universal across countries with different histories of democratic rule. This article examines the extent to which democracy stock (the accumulated amount of democratic traditions, legacies, and experiences consolidated over time) conditions the relationship between education and blind patriotism. Using international data from 33 countries, the article shows that the remedial effect of education is more pronounced in countries with larger stocks of democracy than in countries with higher levels of democracy (current or recent). The results imply that the political socialization of critical patriotism is a cumulative process in which citizens internalize their potentially democratic competencies (e.g., knowledge, skills, and dispositions) and develop a sense of national attachment based on critical reflection on government policy and practice (i.e., critical loyalty) over an extended period of time.     

Canonical analysis of two convex polyhedral cones and applications

Canonical analysis of two convex polyhedral cones consists in looking for two vectors (one in each cone) whose square cosine is a maximum. This paper presents new results about the properties of the optimal solution to this problem, and also discusses in detail the convergence of an alternating least squares algorithm. The set of scalings of an ordinal variable is a convex polyhedral cone, which thus plays an important role in optimal scaling methods for the analysis of ordinal data. Monotone analysis of variance, and correspondence analysis subject to an ordinal constraint on one of the factors are both canonical analyses of a convex polyhedral cone and a subspace. Optimal multiple regression of a dependent ordinal variable on a set of independent ordinal variables is a canonical analysis of two convex polyhedral cones as long as the signs of the regression coefficients are given. We discuss these three situations and illustrate them by examples.     

A method of optimal scaling for multivariate ordinal data and its extensions

This paper develops a method of optimal scaling for multivariate ordinal data, in the framework of a generalized principal component analysis. This method yields a multidimensional configuration of items, a unidimensional scale of category weights for each item and, optionally, a multidimensional configuration of subjects. The computation is performed by alternately solving an eigenvalue problem and executing a quasi-Newton projection method. The algorithm is extended for analysis of data with mixed measurement levels or for analysis with a combined weighting of items. Numerical examples and simulations are provided. The algorithm is discussed and compared with some related methods.Earlier results of this research appeared in Saito and Otsu (1983). The authors would like to acknowledge the helpful comments and encouragement of the editor.     

Functional measurement approach to self-estimation in multiattribute evaluation

Multiattribute analysis depends on measurement of values and weights. Unless these measures reflect the decision maker's true values and weights, the multiattribute formula may put a less-preferred alternative in first place. To avoid such disordinality requires stringent measurement conditions: First, the values and weights must be on linear (equal interval) or ratio (known zero) scales. Second, these scales must satisfy a condition of common unit across disparate attribute dimensions. Most methods of range adjustment beg both of these measurement questions. Functional measurement theory can solve both problems and so can be useful in multiattribute analysis. Past work has established the operation of a general cognitive algebra as an empirical reality. The averaging model, in particular, makes possible the definition and estimation of weights and values as distinct psychological parameters. It can also solve the problem of common unit. Cognitive algebra thus provides a grounded theoretical foundation on which to develop self-estimation methodology, in which decision makers provide direct estimates of their values and weights. The logic is straightforward. Functional measurement can analyze global judgments to obtain validated psychological scales. These scales may then be used as validational criteria for the self-estimates. Procedures to eliminate biases in the self-estimates can thus be tested and refined in well-learned multiattribute tasks, such as judgments of meals, in which global judgments are trustworthy. Once developed, such self-estimation procedures may be used with some confidence for general multiattribute analysis. A number of studies from 20-odd years of work on the theory of information integration are summarized to show good, although not unmixed promise for self-estimation.     

Confidence in judgments based on incomplete information: An investigation using both hypothetical and real gambles

This study assessed how confidence in judgments is affected by the need to make inferences about missing information. Subjects indicated their likelihood of taking each of a series of gambles based on both probability and payoff information or only one of these sources of information. They also rated their confidence in each likelihood judgment. Subjects in the Explicit Inference condition were asked to explicitly estimate the values of missing information before making their responses while subjects in the Implicit Inference condition were not. The manner in which probability information was framed was also manipulated. Experiment 1 employed hypothetical gambles and Experiment 2 employed gambles with real money. Expressed likelihood of taking gambles was higher when probability was phrased in terms of '% chance of winning' rather than '% chance of losing', but this difference was somewhat less with real gambles than with hypothetical gambles. Confidence ratings in each experiment were actually higher on incomplete information trials than on complete information trials in the Explicit Inference condition. Results were related to the general issue of confidence in judgments.     

Effectiveness of the GOFER course in decision making for high school students

The paper describes and evaluates the GOFER course in decision making for high school students (Mann, Harmoni and Power, 1988). The course was based on principles from the conflict theory of decision making (Janis and Mann, 1977) and was designed to provide adolescents with an understanding of factors that produce good and poor decision making as well as knowledge and practice of sound decision skills. Two evaluation studies were conducted to examine effectiveness of the course. Study 1 was conducted with young adolescents (12 year olds). It found a significant difference between students trained in the course and a control group on measures of self-esteem as a decision maker, self reported decision habits and knowledge of decision strategy. Study 2 was conducted with mid-adolescents (15 year olds). It, too, found a significant difference between students who took the course and a control group on measures of self esteem as a decision maker and self-reported decision habits. It is concluded that while the evaluation study fell short of an ideal test, the GOFER course met the criteria of improving student knowledge, raising confidence in decision making and changing self reported decision habits.