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² In order to determine the total number of New York agencies, the New York State Directory was consulted. The Directory, arranged by organizational members as well as by structural units, helped determine agencies which, by definition, are assumed to be information-intensive. A second, more detailed scan of internal organizational structure determined those units which are information-intensive yet lack visibility. The following agencies were selected for analysis: Department of Agriculture and Markets Atmospheric Sciences Research Center Division of the Budget Department of Commerce Office of Drug Abuse Services New York State Energy Office New York State Energy Research and Development Administration Department of Environmental Conservation Department of Health Higher Education Services Corporation Department of Mental Hygiene Department of Motor Vehicles Department of Public Service Research Foundation of the State University of New York Legislative Commission on Science and Technology New York State Science and Technology Foundation Department of Social Services Division of State Police Department of Transportation

³ The selection of individuals for the survey population was accomplished by using three procedures. First, key administrators located in the various organizations were asked to provide a comprehensive listing of people within their organizations who could be regarded as "professional" (defined as one who engages in a non-routine, non-processing activity or series of activities which are often directed toward problem-solving). Second, these administrators were asked to provide names of individuals outside the formal organizational-unit structure with whom they frequently interacted, both formally and informally. Third, the researcher consulted available organizational directories which included specific titles and names.

⁴ The statistical measure, Kendall's tau, is suitable for the analysis of primary ordinal level data used in this study. Rather than choose an alternative measure, such as Spearman's rho, Somer's d, Goodman and Kruskal's gamma, the assumption was made—based on the sample size—that the data may contain a large number of tied ranks. Use of Kendall's tau is, therefore, appropriate under these circumstances.

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