<?xml version="1.0" encoding="UTF-8"?><rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcq="http://purl.org/dc/terms/"><records count="1" morepages="false" start="1" end="1"><record rownumber="1"><dc:product_type>Conference Paper</dc:product_type><dc:title>How We Code</dc:title><dc:creator>Shaffer, David W.; Ruis, Andrew R.</dc:creator><dc:corporate_author/><dc:editor>Ruis, Andrew R.; Lee, Seung B.</dc:editor><dc:description>Coding data—defining concepts and identifying where they occur in
data—is a critical aspect of qualitative data analysis, and especially so in
quantitative ethnography. Coding is a central process for creating meaning from
data, and while much has been written about coding methods and theory,
relatively little has been written about what constitutes best practices for fair and
valid coding, what justifies those practices, and how to implement them. In this
paper, our goal is not to address these issues comprehensively, but to provide
guidelines for good coding practice and to highlight some of the issues and key
questions that quantitative ethnographers and other researchers should consider
when coding data.</dc:description><dc:publisher/><dc:date>2021-01-01</dc:date><dc:nsf_par_id>10248625</dc:nsf_par_id><dc:journal_name>Advances in Quantitative Ethnography: Second International Conference, ICQE 2020, Malibu, CA, USA, February 1-3, 2021, Proceedings</dc:journal_name><dc:journal_volume/><dc:journal_issue/><dc:page_range_or_elocation>62 - 77</dc:page_range_or_elocation><dc:issn/><dc:isbn/><dc:doi>https://doi.org/https://doi.org/10.1007/978-3-030-67788-6_5</dc:doi><dcq:identifierAwardId>1661036</dcq:identifierAwardId><dc:subject/><dc:version_number/><dc:location/><dc:rights/><dc:institution/><dc:sponsoring_org>National Science Foundation</dc:sponsoring_org></record></records></rdf:RDF>