A Response From Golden Rule to "ETS on 'Golden Rule'"

In this rejoinder to Anrig's criticisms in the last issue of EM, Rooneg responds to Anrig's arguments and reasserts his position that the Golden Rule settlement was necessarg and reasonable and has been effective.     

On Becoming Allies: A Qualitative Study of Lesbian‐, Gay‐, and Bisexual‐Affirmative Counselor Training

The authors present a qualitative analysis of a process by which a research team of counselors‐in‐training confronted their heterosexist biases while investigating heterosexual attitudes toward sexual minorities. Members of the research team discovered that it was essential to reflect on and evaluate their attitudes, assumptions, and biases before they could conduct scientific research about affirmative attitudes toward lesbian, gay male, and bisexual male and female individuals. Self‐reflective narratives written by each research team member were analyzed using consensual qualitative research methodology. Results yielded 10 general categories or themes. Implications for counseling theory, training, and future research are discussed.     

A scaleable document clustering approach for large document corpora

In this paper, the scalability and quality of the contextual document clustering (CDC) approach is demonstrated for large data-sets using the whole Reuters Corpus Volume 1 (RCV1) collection. CDC is a form of distributional clustering, which automatically discovers contexts of narrow scope within a document corpus. These contexts act as attractors for clustering documents that are semantically related to each other. Once clustered, the documents are organized into a minimum spanning tree so that the topical similarity of adjacent documents within this structure can be assessed. The pre-defined categories from three different document category sets are used to assess the quality of CDC in terms of its ability to group and structure semantically related documents given the contexts. Quality is evaluated based on two factors, the category overlap between adjacent documents within a cluster, and how well a representative document categorizes all the other documents within a cluster. As the RCV1 collection was collated in a time ordered fashion, it was possible to assess the stability of clusters formed from documents within one time interval when presented with new unseen documents at subsequent time intervals. We demonstrate that CDC is a powerful and scaleable technique with the ability to create stable clusters of high quality. Additionally, to our knowledge this is the first time that a collection as large as RCV1 has been analyzed in its entirety using a static clustering approach.