Edited By Do Kyun Kim and James W. Dearing
Social science theorists have long envisioned how social scientists could organize so that the knowledge borne from our work might contribute to the improvement of both science and society (Campbell, 1971; Cronbach, 1982). Such aspiration requires that researchers understand what their forefathers did before them and with what results so that we may incrementally improve (Merton, 1965). In the health promotion field, progress in this direction has occurred, for example, through the production of consensus statements about standards of evidence (Flay et al., 2005).
Alas, the challenge of learning incrementally and cumulatively from others’ work is daunting. Not only are we limited in terms of how much each of us can know (Simon, 1955), but the expansion of scientific knowledge continues unabated. We publish our results in more journals than ever before and increasingly cite others’ work that appears in new and far flung journals (Acharya et al., 2014). If modern society can be thought of as an information processor, then it is at present an increasingly decentralized one.
Researchers and policy makers who attend to issues of research measurement have attempted to coalesce what we know. For certain measures, compendiums exist of their validity, reliability, long and short forms, and adaptations to suit particular applications or topics, along with examples for how to use them and interpret results (Kiresuk, Smith, & Cardillo, 1994). Online resources such as the Measurement Instrument Database for the Social Sciences do not as of yet cover much of...
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