Though there are different interpretations in the scholarly literature of what a social learning is: whether it is an individual, organisational, or collective process. For example, Freeman (2007), in his study on policy change in the public health sector, conceptualised collective learning of public officials as a process of epistemological bricolage. In his interpretation, the new policy ideas are the result of this bricolage process, when the “acquired second-hand” ideas are transformed into “something new”. The literature on (democratic) governance points opens another perspective to the policy change, emphasising the importance of public engagement in the policy-making process. Following this school of thought the new policy is the result of a deliberative act that involves different participants. In other words, the ideas about policy are not borrowed, but are born in social deliberation. Combining the insights gained from both literatures – social learning and governance – the policy change is interpreted, as a result of a broad social interaction process, which is also the social learning for all participants.The paper will focus on further development of the conceptualisation of policy change through social deliberation and social learning and will attempt to define the involved micro mechanisms. The exploratory case study of policy change that was preceded by a broad public debate will help to describe and establish the mechanisms. Specifically, the paper will focus on the decision of the Dutch government to cease the exploration of natural gas from the Groningen gas field. The radical change in national policy regarding gas exploration is seen as a result of a broader public debate, which was an act of social deliberation and social learning at the same time.
DOCUMENT
Frank Jan de Graaf invites us to try on deliberative practices. Firmly rooted in pragmatism, deliberation has historically played a significant (some say central) role in democratic societies. It also comes in handy when opposite perspectives invite us to summon new ways to converse about issues that matter — but matter differently to each of us. Rather than bracing against those who don’t share a particular purpose, de Graaf advocates for open dialogue, so we begin to look beyond the current divides and discover integrative ways to develop new rules of engagement, frame new responsibilities, and discover new solutions.
LINK
Abstract for World Physiotherapy Congress 2021Title Ethical Considerations of Using Machine Learning for Decision Support in Occupational Physical Therapy: a narrative literature study and ethical deliberation. Authors Marianne W. M. C. Six Dijkstra1,4,7 · Egbert Siebrand2 · Steven Dorrestijn2 · Etto L. Salomons3 ·Michiel F. Reneman4 · Frits G. J. Oosterveld1 · Remko Soer1,5 · Douglas P. Gross6 · Hendrik J. Bieleman1 Presenter and contactName: Marianne W. M. C. Six DijkstraEmail: w.m.c.sixdijkstra@saxion.nlAdres: School of Health, Saxion University of Applied Sciences/AGZ, M.H. Tromplaan 28, 7500 KB, Enschede, The NetherlandsTel: +31(0)612379329 1 School of Health, Saxion University of AppliedSciences, Enschede, The Netherlands2 Research Group Ethics & Technology, Saxion Universityof Applied Sciences, Enschede, The Netherlands3 School of Ambient Intelligence, Saxion Universityof Applied Sciences, Enschede, The Netherlands4 Department of Rehabilitation Medicine, University MedicalCenter Groningen, University of Groningen, Groningen,The Netherlands5 University Medical Center Groningen, Pain Centre,University of Groningen, Groningen, The Netherlands6 Department of Physical Therapy, University of Alberta,Edmonton, Canada7 University of Groningen, Groningen, The Netherlands Funding This study was funded by Netherlands Organisation for Scientific Research (NWO) (023.011.076) and Saxion University of Applied Sciences in The Netherlands. The funding source had no involvementin study design, data collection, analysis or interpretation, in the writing of the report, or the decision to submit the article for publication.Ethical approvalThis study is part of a PhD project entitled “Development of a Decision Support System – Artificial Intelligence advices for Sustainable Employability”. The Ethics Board at the University Medical Center Groningen in The Netherlands decided that formal approval of the study was not necessary because all workers were subjected to care as usual only.AbstractBackground Computer algorithms and Machine Learning (ML) will be integrated into clinical decision support within physical therapy. This will change the interaction between therapists and their clients, with unknown consequences.Purpose The aim of this study was to explore ethical considerations and potential consequences of using ML based decision support tools (DSTs). We used an example in the context of occupational physical therapy.Methods We conducted an ethical deliberation. This was supported by a narrative literature review of publications about ML and DSTs in occupational health and by an assessment of the potential impact of ML-DSTs according to frameworks from medical ethics and philosophy of technology. We introduce a hypothetical clinical scenario in occupational physical therapy to reflect on biomedical ethical principles: respect for autonomy, beneficence, non-maleficence and justice. The reflection was guided by the Product Impact Tool.
MULTIFILE
