<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">De Bal, Inge</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">From one to many: generalisation and evidence in failure analysis.</style></title></titles><dates><year><style  face="normal" font="default" size="100%">Submitted</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In this paper, I use cases and reasoning from failure analysis (a part of engineering&lt;br /&gt;science which deals with artefact failure and its causes) to draw attention to a relatively&lt;br /&gt;unstudied problem of knowledge generalisation: when we are focusing on creating new&lt;br /&gt;things; designing new artefacts and technologies. Using three cases from failure&lt;br /&gt;analysis practice, I present a two-fold mechanism-based procedure to determine when&lt;br /&gt;generalisations to non-existing artefacts are warranted. This procedure builds on (1)&lt;br /&gt;Cartwright's notion of capacities (2) literature on mechanisms and (3) Steel's&lt;br /&gt;comparative process tracing, developed for the biomedical sciences. I will show that,&lt;br /&gt;while they provide guidance, these literatures and concepts are not enough to grasp&lt;br /&gt;how we use information from current artefacts and failures to create new things - we&lt;br /&gt;will need a lot more specific information and adequate ways to present it. The account&lt;br /&gt;developed in this paper is relevant for both philosophers and failure analysts. For&lt;br /&gt;philosophers, it can provide input for a theory of evidence. For failure analysts, it allows&lt;br /&gt;them to present stronger arguments for their recommendations by making the required&lt;br /&gt;evidence explicit. My account can furthermore provide inspiration for similar inferences&lt;br /&gt;in other innovation contexts such as pharmacology.&lt;/p&gt;</style></abstract></record></records></xml>