Reference : Representations of Incident Reporting as a Collective Learning Process
Scientific congresses and symposiums : Unpublished conference/Abstract
Law, criminology & political science : Political science, public administration & international relations
Social & behavioral sciences, psychology : Sociology & social sciences
http://hdl.handle.net/2268/166469
Representations of Incident Reporting as a Collective Learning Process
English
Rossignol, Nicolas mailto [Université de Liège - ULiège > Département de science politique > Anal. et éval. des politiques publ.-Méthod. de sc. politique >]
Turcanu, Catrinel mailto []
Jun-2014
Yes
International
The 23rd SRA-Europe conference
from 16-06-2014 to 18-06-214
SRA-Europe
Istanbul
Turkey
[en] Vulnerability ; Incident Reporting System
[en] In the context of vulnerability analysis, it is now widely aknowledged that social factors should be taken into account, alongside technical ones. Depending on the particular approach adopted, these social factors are considered to influence “coping capacities”, “adaptive capacities” or “resilience”. The ability of a socio-technical system to learn from past incidents and accidents seems to have a positive influence on its vulnerability, as it increases its capacity to adapt properly in case of future unwanted envents. To that regard, incident reporting systems are of first importance as they are supposed to constitute a collective memory of past incidents, to initiate a collective share of information and to foster collective learning and adapations. Yet, the theoretical assumptions about the ability of a reporting system to imply collective learning have still to be demonstrated. This paper proposes a methodology addressing this issue. To do so, we conduct a number of semi-structured interviews in a nuclear facility with various types of actors (managers, lab responsibles, technical workers), and in different risk contexts. In addition, participants are requested to produce a mental map of the reporting system they are concerned with. These inputs are then analyzed following a “cross-case analysis” procedure in order to identify patterns of actors' representations of the reporting system, and to link these patterns to potential learning processes fostered by the system. This constitutes the first step of an inductive research process aiming to identify and characterize the link between reporting systems and collective learning. In the next steps, the link between the identified patterns of representations and collective learning processes will be tested quantitatively. The final aim being to elaborate ways to improve Incident Reporting Systems to improve collective learning.
SPIRAL
GdF-Suez
Researchers ; Professionals ; Students
http://hdl.handle.net/2268/166469

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