Disagreement in discipline-building processes.
Successful instances of interdisciplinary collaboration can eventually enter a process of disciplinarisation. This article analyses one of those instances: agent-based computational social science, an emerging disciplinary field articulated around the use of computational models to study social phen...
| Publicado en: | Synthese Vol. 198; no. 25; pp. 6201 - 6225 |
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| Formato: | Artículo |
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Springer Nature
Nov2021 Supplement 25
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=153553281&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 153553281 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00397857 4LI jtl: Synthese issn: 00397857 maglogo: N pubinfo: dt: Nov2021 Supplement 25 vid: 198 iid: 25 pid: 237 pub: Springer Nature artinfo: ui: 153553281 10.1007/s11229-019-02438-9 ppf: 6201 ppct: 24 formats: fmt: @attributes: type: P size: 369KB tig: atl: Disagreement in discipline-building processes. aug: au: Anzola, David affil: Innovation Center, School of Management, Universidad del Rosario, Bogotá, Colombia su: Knowledge transfer Social facts Dualism sug: subj: Knowledge transfer Social facts Dualism keyword: Agent-based modelling Disagreements Disciplinary identity Discipline-building Interdisciplinarity Shared commitments ab: Successful instances of interdisciplinary collaboration can eventually enter a process of disciplinarisation. This article analyses one of those instances: agent-based computational social science, an emerging disciplinary field articulated around the use of computational models to study social phenomena. The discussion centres on how, in knowledge transfer dynamics from traditional disciplinary areas, practitioners parsed several epistemic resources to produce new foundational disciplinary shared commitments, and how disagreements operated as a mechanism of differentiation in their production. Two parsing processes are examined to illustrate this claim. The first one is the parsing of the qualitative–quantitative dualism, arguably the most important methodological disagreement in social science. The second one is the parsing of prediction, a key value in contemporary science. The analysis evidences that disagreements have fostered both external and internal dynamics of differentiation in agent-based computational social science. The former have permitted a more efficient use of epistemic resources, whereas the latter have forced practitioners to modify the foundational narrative and the agenda of the field. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Synthese is a copyright of Springer, 2021. All Rights Reserved. item: Synthese holder: Springer Nature dt: @attributes: year: 2021 holdings: @attributes: islocal: N |
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