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Cobb, Casey D.; Rallis, Sharon F. – Leadership and Policy in Schools, 2008
The No Child Left Behind Act (NCLB) has provoked more controversy than any previous education legislation in recent decades. Our conceptual analysis was guided by three questions: What do we see happening in the schools? What does the law seem to mean in terms of accountability to different people in the schools? Where is the justice in these…
Descriptors: Federal Legislation, Academic Achievement, Accountability, School Districts
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Cassar, Vincent – Journal of Education and Work, 2008
Work values help to shape cognitions and motivations and are therefore essential in one's process of searching for employment and remaining employable. The present study explored the typical work values preferred by university students in Malta. Gender and faculty differences as well as gender differences within faculties were explored.…
Descriptors: Social Sciences, Foreign Countries, Gender Differences, Humanities
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Ritchie, J. R. Brent – Journal of Leisure Research, 1975
This paper describes an attempt to derive an empiracally based method for the classification of leisure activities. (RC)
Descriptors: Classification, Cluster Analysis, Cluster Grouping, Leisure Time
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Shields, W. S. – Educational and Psychological Measurement, 1974
A procedure for item analysis using distance clustering is described. Items are grouped according to the predominant factors measured, regardless of what they are. The procedure provides an efficient method of treating unanswered items. (Author/RC)
Descriptors: Algorithms, Cluster Grouping, Item Analysis, Models
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Jackson, Douglas N.; Williams, David R. – Journal of Vocational Behavior, 1975
This study was designed to identify the important clusters of occupational groups identifiable from an analysis of the dimensions accounting for similarity in profile shapes among a set of 28 new vocational interest measures. (Author)
Descriptors: Cluster Grouping, Occupational Clusters, Occupations, Research Projects
Yu, Clement T. – Information Storage and Retrieval, 1974
Heuristic methods for the construction of term classes are presented and experimental results are obtained to illustrate the usefulness of the method. (Author/PF)
Descriptors: Algorithms, Automatic Indexing, Classification, Cluster Grouping
Adamson, George W.; Boreham, Jillian – Information Storage and Retrieval, 1974
An automatic classification technique has been developed, based on the character structure of words. (Author)
Descriptors: Automatic Indexing, Automation, Classification, Cluster Grouping
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Crouch, Donald B. – Information Processing and Management, 1975
Describes a clustering algorithm designed for dynamic data bases and presents an update procedure which maintains an effective document classification without reclustering. The effectiveness of the algorithms is demonstrated for a subset of the Cranfield collection. (Author)
Descriptors: Automatic Indexing, Cluster Grouping, Databases, Information Retrieval
Bureau of the Census (DOC), Suitland, MD. Population Div. – 1971
This index was developed primarily to define the industrial and occupational classification systems adopted for the 1970 Census of Population. For each category in the classification systems it presents the individual titles constituting the particular category. Approximately 19,000 industry and 23,000 occupation titles are included. These titles…
Descriptors: Classification, Cluster Grouping, Codification, Indexes
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Halff, Henry M. – 1975
Graphical methods for evaluating the fit of Johnson's hierarchical clustering schemes are presented together with an example. These evaluation methods examine the extent to which the clustering algorithm can minimize the overlap of the distributions of intracluster and intercluster distances. (Author)
Descriptors: Classification, Cluster Analysis, Cluster Grouping, Graphs
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Harvey, Robert J. – Personnel Psychology, 1986
Addresses selecting among and using the numerous quantitative job classification procedures, with a focus on the decision-making tasks and practical difficulties that confront users of each. (Author/ABB)
Descriptors: Classification, Cluster Grouping, Decision Making, Job Analysis
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Murtagh, F. – Information Processing and Management, 1984
Using examples of data from the areas of information retrieval and of multivariate data analysis, six hierarchic clustering algorithms (single link, median, centroid, group average, complete link, Wards's) are examined and evaluated by using three proposed coefficients of hierarchic structure. Nine references are cited. (EJS)
Descriptors: Algorithms, Cluster Analysis, Cluster Grouping, Data Analysis
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Yu, C. T. – Journal of the American Society for Information Science, 1976
A measure for the quantification of the changes in classification under small changes in data is proposed. (Author)
Descriptors: Classification, Cluster Analysis, Cluster Grouping, Information Retrieval
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So, Tak-Shing Harry; Peng, Chao-Ying Joanne – 2002
This study compared the accuracy of predicting two-group membership obtained from K-means clustering with those derived from linear probability modeling, linear discriminant function, and logistic regression under various data properties. Multivariate normally distributed populations were simulated based on combinations of population proportions,…
Descriptors: Cluster Grouping, Group Membership, Prediction, Probability
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Henschke, C. I.; Chen, M. M. – Journal of Educational and Psychological Measurement, 1974
Descriptors: Classification, Cluster Grouping, Multiple Regression Analysis, Selection
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