Description
Book SynopsisAll data are the result of human actions whether by experimentations, observations, or declarations. As such, the presumption of knowing what data are about is subject to imperfections that can affect the validity of research efforts. With calls for data-based research comes the need to assure the reliability of generated data. The reliability of converting texts into analyzable data has become a burning issue in several areas. However, this issue has been met by only a few limited, and sometimes misleading measures of the extent to which data can be trusted as surrogates of the phenomena of analytical interests. The statistic proposed by the author â Krippendorffâs Alpha â is widely used in the social sciences, not only where human judgements are involved but also where measurements are compared.
The Reliability of Generating Data expands on the authorâs seminal work in content analysis and develops methods for assessing the reliability of the kind
Table of Contents
How I became interested in reliability issues. 1. On the epistemology of reliable data. 2. Simplest kinds: The replicability of categorizing predefined units. 3. Some properties of the Alpha. 4. Alpha compared with primarily nominal agreement measures. 5. Metric differences between single-valued units.6. The quadrilogy for single-valued predefined units and big data. 7. Multi-valued coding of predefined units.8. Partitioning continua and coding relevant segments. 9. Preserving the coherency of identified segments in continua. 10. Distinctions drawn within continua. 11. Text mining and information retrieval. 12. Diagnostic devices and remedial actions. 13. Some special applications. 14. Statistical considerations. 15. Reliability standards. 16. Toward a general calculus of differences and agreements. Appendix. References
