CROWDING,TASK PERFORMANCE,AND COMMUNICATIVE INTERACTION IN YOUTH AND OLD AGE

Following Altman's privacy regulation model, this research was based on the assumption that the relationship between achieved and desired levels of privacy is a major determinant of the experience of crowding in small groups. Further, on the basis of evidence that advancing age is associated with a chronic lack of communicative interaction, it was assumed that the achieved level of privacy among elderly persons generally is greater than that experienced by young adults. Given these assumptions, it was predicted that the crowding threshold of young adults would be significantly lower than that of older persons. To test this hypothesis, the research varied conversation distance (close, far) and density (small room, large room) and assessed the quality of communicative interaction and task performance among small groups of college-age females and retired women over 60 years of age. Results showed that task performance among younger subjects deteriorated in close interaction conditions, whereas the performance of older subjects was improved by spatial intrusion. Further, older subjects exhibited positive communication behaviors in response to close conversation, high-density conditions, while younger subjects responded either with negative communication behaviors or were unaffected by spatial restriction. Finally, the research confirmed previous findings that conversation distance is a more important determinant of the experience of crowding in small groups than physical density. The significance of the results for Altman's privacy regulation model and their implications for the study of human communication behaviors were discussed.     

Change of preferences under time pressure: choices and judgements

Students made choices between student apartments judged to be equally attractive. When asked to choose the best apartment in each pair of alternatives, choices made by a group under time pressure were significantly different from those made by another group under no time pressure. The effect was so strong that preference reversals were obtained which could be explained by subjects over-evaluating negative aspects on the most important attribute under time pressure.     

SCALING PERFORMANCE UTILITY TO ENHANCE SELECTION/CLASSIFICATION DECISIONS

For purposes of selection and classification there are two general reasons for scaling the mean and variance of the utility of performance across jobs. First, if differential utility across jobs does exist, then the payoff from a selection and classification system will be enhanced to the extent that accurate utility values are incorporated in the assignment system. Second, a valid utility metric would permit a more meaningful comparison of the gains achieved by alternative selection and classification procedures. It is argued in this paper that the Army context, and perhaps others, precludes using the dollar metric and estimates of SD_y in dollars. Consequently, Project A conducted a relatively long series of exploratory workshops with Army personnel to (a) define the utility issue, (b) pilot test a wide variety of possible scaling methods, and (c) evaluate the methods that seemed most appropriate. On the basis of exploratory analysis, a combined procedure incorporating both an interval estimation and a ratio estimation method was used to estimate the utility of five different performance levels for each of 276 jobs (MOS) in the enlisted personnel system. The psychometric properties of the resulting scale values are analyzed and discussed.     

MODELING JOB PERFORMANCE IN A POPULATION OF JOBS

The Army Selection and Classification Project has produced a comprehensive examination of job performance in 19 entry-level Army jobs (Military Occupational Specialties) sampled from the existing population of entry-level positions. Multiple methods of job analysis and criterion measurement were utilized in a subsample of nine jobs to generate over 200 performance indicators, which were then used to assess performance in a combined sample of 9,430 job incumbents. An iterative procedure involving a series of content analyses and principal components analyses was used to develop a basic array of up to 32 criterion scores for each job. This basic set of scores formed the starting point of an attempt to model the latent structure of performance in this population of jobs. After alternative models were proposed for the latent structure, the models were submitted to a goodness-of-fit test via LIS-REL VI. After accounting for two components of method variance, a five-factor solution was judged as the best fit. The implications of the results and the modeling procedure for future personnel research are discussed.