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Excerpted from my book Generally Speaking, this paper introduces "concept‐driven sociology," a special way of theorizing designed to reveal abstract social patterns. As such, it examines the methodological process by which we can "distill" generic patterns from the culturally, historically, and situationally specific contexts in which we encounter them. It thus champions a "generic sociology" that is pronouncedly transcontextual (transcultural, transhistorical, transsituational, and translevel) in its scope. In order to uncover generic, transcontextual social patterns, we need to collect our data in a wide range of social contexts. Such contextual diversity is manifested multi‐culturally, multihistorically, multisituationally, as well as at multiple levels of social aggregation. True to its message, the book illustrates generic social patterns by drawing on numerous examples from diverse cultural contexts and historical periods and a wide range of diverse social domains, as well as by disregarding scale. Emphasizing cross‐contextual commonality, concept‐driven sociology tries to reveal formal "parallels" across seemingly disparate contexts. The paper features the four main types of cross‐contextual analogies concept‐driven sociologists tend to use—cross‐cultural, cross‐historical, cross‐domain, as well as cross‐level—disregarding conventionally noted substantive differences in order to note conventionally disregarded formal equivalences. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate the usefulness of examples that show typical learner errors in online pedagogical dictionaries of English for the accuracy of error correction as well as immediate and delayed retention of usage. The optimal positioning of examples of errors in entries is also researched. In an online experiment, participants did a sentence correction exercise with the help of purpose-built monolingual dictionary entries, where the provision and positioning of examples showing errors were controlled. Two test versions were created, which differed only in the presence of examples of errors in the entries. Usage retention was observed immediately after the test and two weeks later. The results indicate that it is worthwhile to include examples of errors in online learners' dictionaries because they contribute greatly to the retention of usage in the long run. They also help to rectify errors, though the effect is not statistically significant. The positioning of examples showing errors in entries has no influence on error correction accuracy or usage retention. The study reveals examples of errors to be a valuable induction-oriented stand-alone dictionary component placed outside warning boxes, which typically include explicit grammar rules and promote deduction. [ABSTRACT FROM AUTHOR]