The attitudes towards sexual relationships among persons with learning disabilities (PLD) of parents of children without disabilities were compared with the attitudes of family caregivers (parents of PLD) and with the attitude of professional caregivers. The importance of different situational factors that may alter acceptability judgments (i.e., gender, etiology of the disability, person's present level of autonomy, use of contraceptive devices, and partner's age and possible handicap) with regards to the sexuality of PLD was examined through the use of concrete cases. All the participants lived in Mexico. The only notable difference in attitude that was observed was between parents of PLD suffering from trisomia 21 and parents of PLD suffering from a neuromotor disorder. As a result, it may be erroneous to consider parents of PLD as a homogeneous group regarding attitudes to sexuality. Three different basic philosophies regarding the expression of sexuality among PLD were observed. They were called Mainly Unacceptable (37% of the sample), Mainly Acceptable (36%), and Depending on Circumstances (27%). In this later philosophy, contraception was by far the major determinant of acceptability.

A menu-driven software system was developed to implement schemata organization in a constraintsatisfaction neural network. The current neural-net model presents several advantages and modifications over previous related models. On the one hand, the schemata behavior shown by the present model is based on conceptual definitions and ratings obtained empirically from human subjects rather than on the idiosyncratic knowledge database of a single programmer. On the other hand, this property is most valuable to experimental research in which the current knowledge status of the subjects is critical for the experiments (e.g., word-recognition experiments).The present paper describes a menu-driven software system called Semantic Analyzer of Schemata Organization (SASO). This program was developed to implement schemata organization in a constraint-satisfaction neural network similar to the connectionist model for schemata postulated by Rumelhart, Smolensky, McClelland, and Hinton in 1986. However, the current neural-net model presents several advantages and modifications over previous related models. First, the schemata behavior shown by the present neural net is based on conceptual definitions and ratings obtained empirically from human subjects rather than on the idiosyncratic knowledge database of a single programmer. This property is especially well suited to experimental research in which the knowledge status of the subjects is critical for the experiments (e.g. , word-recognition experiments). Second, SASO provides the user with a set of utilities to process raw data generated by the subjects. It also automatically sets up the weight-connectivity matrix among concepts and generates the interface data files needed to run schemata simulations on the constraint-satisfaction neural-net program provided by McClelland and Rumelhart in 1988. A psychological experiment and computer neural-net simulations were carried out to test schemata organization in the current neural-net model. Furthermore, some statistical analysis was performed on the weight-eonnectivity matrix of the neural net. The advantages of using the current model as a computational tool for psychological experiments will be argued elsewhere in this paper, ANALYSIS AND SCALING OF CONCEPTUAL DEF1NITIONSThe first part of the study obtained the empirical data that were used in the neural-network simulations. The schema of room and related schemata were chosen for this experiment in order to work with some of the same schemata that Rumelhart et al. (1986) used in their simulations and thus be able to compare results. Rumelhart et al. (1986) chose a priori the descriptor concepts implemented in their network. By contrast, in the present study, a technique to obtain semantic networks from subjects was used to obtain the concepts of the neural network. Thus, the current schemata simulations are based on the information generated from the memories of a sample of 24 undergraduate students. The technique to obtain conceptual definitions is illustrated in the Method sec...

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Attitudes towards regular school inclusion of people with intellectual disabilities (ID) are affected by factors such as disability severity, educational level, and teacher experience. Nevertheless, the ways that teachers integrate these factors to form inclusion judgments remains unclear. The current paper explores what systematic cognitive algebra rules are used to cognitively integrate this set of inclusion factors by special education teachers and psychology students. To do so, 469 special education teachers and psychology students were asked to take part in two experimental cognitive algebra studies. In each study, participants had to read a set of school inclusion scenarios and rate the probability that a scenario actor with ID could be successfully integrated into a regular school program. To this purpose, factor effects on successful school inclusion and ID related to individuality, situational aspects, and contextual considerations (e.g., school environment, grade level taught) were explored. Results suggested that participants showed attitudes to school inclusion ranking from light to moderate positive values. Situational factors, as well as context factors, were judged to be more significant than other factors in elementary education. These factors were integrated by following a cognitive summative rule. Overall, judgment for successful school inclusion follows a summative rule to integrate sources of information. This rule is maintained irrespective of the disability under consideration. However, valuation of each source of information does depend on the type of the current study sample. Implications of these results for inclusion of people with disabilities in regular schools are discussed in this paper.