Spatial familiarity is a natural language concept that has no well-defined technical interpretation. W e explore here some possible dimensions of the concept, provide subjective measurements of the dimensions, and evaluate their independence. The four dimensions examined are locational knowledge, visual recognition, name identification, and interaction frequency. W e suggest that both cognitive and behavioral dimensions are embedded in the concept of spatial familiarity and must be part of the meaning of the concept and of any attempt to make it operational.

Hierarchical clustering, Choropleth mapping, Matrix reorganization, Unidimensional seriation, Ordered binary trees,

Following the first AAG departmental survey (Spring, 1981), the AAG Committee on the Status of Women undertook a subsequent study in Winter and Spring Quarters, 1982; 60 departments participated. A brief questionnaire was sent to the Chairpersons asking for basic information on the characteristics of women in the discipline.Even the simple questions required a substantial degree of effort and perseverance and temporal data were difficult to obtain for most departments. Attempts to determine why students failed to complete their degrees, or why they chose places to work, and their opinions on the existence of harassment and discrimination encountered difficulty in obtaining responses. Nevertheless, 57 of the 60 departments canvassed responded with varying degrees of completeness. The purpose here is to report the results and to highlight the need to collect and interpret more information about this sub-group of geographers. We do not intend to discuss women's issues in depth; other papers (e.g., by Hanson and Monk, and others in the Special Feature on Women in the February 1982 PC) do this well.

No abstract

An inference strategy is presented to assess the goodness-of-fit for logit models. The conventional approach has emphasized likelihood ratio tests in which a distribution for the test statistic is assumed. A more recent development, the prediction success table, is based upon a ratio of predicted to observed choice patterns, yet it is primarily a descriptive index not placed within the context of an inference strategy/hypothesis-testing framework. An alternative method is put forward which uses residuals. Although problematic in a parametric context, residuals can be used in an approach which incorporates both a nonparametric randomization procedure and a sample reuse design. A test statistic is defined and compared to a reference distribution created under the assumption of random variation in the responses with variation in the explanatory variable(s). A numerical example is carried out to investigate the efficacy of using this approach.