Further experimental analysis of the social learning and transmission of foraging information amongst Norway rats

1992 ◽  
Vol 27 (1) ◽  
pp. 53-64 ◽  
Author(s):  
K.N. Laland ◽  
H.C. Plotkin
Keyword(s):  
Social Learning ◽  
Experimental Analysis ◽  
The Social ◽  
Norway Rats

Social Learning about Environmental Innovations: Experimental Analysis of Adoption Timing

2017 ◽  
Vol 7 (1-2) ◽  
pp. 135-178
Author(s):  
Julian Jamison ◽  
David Owens ◽  
Glenn Woroch
Keyword(s):  
Social Learning ◽  
Experimental Analysis

scholarly journals Achieving Social and Ecological Outcomes in Collaborative Environmental Governance: Good Examples from Swedish Moose Management

2021 ◽  
Vol 13 (4) ◽  
pp. 2329
Author(s):  
Sabrina Dressel ◽  
Annelie Sjölander-Lindqvist ◽  
Maria Johansson ◽  
Göran Ericsson ◽  
Camilla Sandström
Keyword(s):  
Social Learning ◽  
Environmental Governance ◽  
Collaborative Governance ◽  
Theory Of Change ◽  
Ecological Context ◽  
Discretionary Power ◽  
Structured Interviews ◽  
Resource Governance ◽  
Social Ecological ◽  
The Social

Collaborative governance approaches have been suggested as strategies to handle wicked environmental problems. Evaluations have found promising examples of effective natural resource governance, but also highlighted the importance of social-ecological context and institutional design. The aim of this study was to identify factors that contribute to the achievement of social and ecological sustainability within Swedish moose (Alces alces) management. In 2012, a multi-level collaborative governance regime was implemented to decrease conflicts among stakeholders. We carried out semi-structured interviews with six ‘good examples’ (i.e., Moose Management Groups that showed positive social and ecological outcomes). We found that ‘good examples’ collectively identified existing knowledge gaps and management challenges and used their discretionary power to develop procedural arrangements that are adapted to the social-ecological context, their theory of change, and attributes of local actors. This contributed to the creation of bridging social capital and principled engagement across governance levels. Thus, our results indicate the existence of higher-order social learning as well as a positive feedback from within-level collaboration dynamics to between-level collaboration. Furthermore, our study illustrates the importance of institutional flexibility to utilize the existing knowledge across stakeholder groups and to allow for adaptations based on the social learning process.

scholarly journals The project “understAID” – a platform that helps informal caregivers to understand and aid their demented relatives

2014 ◽  
Vol 83 (2) ◽  
pp. 182-188
Author(s):  
Elżbieta Skorupska ◽  
Ewa Mojs ◽  
Włodzimierz Samborski ◽  
José C. Millán-Calenti ◽  
Ana Maseda ◽  
...  
Keyword(s):  
Social Learning ◽  
Case Studies ◽  
System Integration ◽  
Informal Caregivers ◽  
Real Case ◽  
International Project ◽  
Formal Caregivers ◽  
Dementia Patients ◽  
The Social

“UnderstAID” is a platform that helps informal caregivers to understand and aid their demented relatives. It is an international project initiated by Denmark, Poland and Spain.The aim of the project is to design, and implement the multimedia platform “understAID” to support informal caregivers of dementia patients. The project was launched in April 2013 and is expected to end 36 months later. The project is divided into five tasks concerning the final aim. The aim of task 1 is the management of the project, as well as the exploitation and dissemination of gathered information. Task 2 is meant to define the contents and solutions of the CarePlatform based on the knowledge gained from real-case studies. Demented elderlies from each country (n = 40) suffering from different degrees of dementia were evaluated by formal caregivers and dementia professionals. The aim of task 3 is the development of the social learning interface. Task 4 focuses on the CarePlatform development and system integration. Finally, task 5 assumes testing and validation of the platform. The platform is devised to be available in two versions, namely the light one for mobile appliance and the premium version. Also different activities leading to the popularization of the platform are planned.

scholarly journals Social Learning Class Topper Optimization (SL-CTO) Based Hop Localization Technique for Wireless Sensor Network

2021 ◽  
Author(s):  
TAPAN KUMAR MOHANTA ◽  
Dushmanta Kumar Das
Keyword(s):  
Social Learning ◽  
Computing Time ◽  
Error Variance ◽  
Localization Error ◽  
Localization Technique ◽  
Current Localization ◽  
The Social ◽  
Rectification Factor ◽  
Network Simulations ◽  
Anisotropic Network

Abstract To address the current situation limitation of traditional DV-Hop, we suggested a DV-Hop localization based on a rectification factor using the Social Learning Class Topper Optimization (SL - CTO) algorithm in that paper. In order to adjust the number of hops between beacon nodes, we have implemented a rectification factor in the suggested method. By measuring the dimensions of all the beacons at dumb nodes, the suggested algorithm decreases communication among unknown or dumb and beacon nodes. The model of network imbalance, It is often considered to be demonstrate a applicability of the Proposed approach in the anisotropic network. Simulations have been performed on LabVIEW@2015, and Comparisons were made with conventional DV-Hop, particle swarm optimization-based DV-Hop and runner-root optimization-based DV-Hop for our proposed algorithm. In comparison to current localization methods, simulation outcomes showed that the proposed localization technique reduces computing time, localization error variance and localization error.

scholarly journals Idea uniwersytetu kształcącego ludzi zaangażowanych w pracę

1970 ◽  
pp. 387-397
Author(s):  
Konrad Kulikowski
Keyword(s):  
Social Learning ◽  
Learning Theory ◽  
Work Engagement ◽  
Social Learning Theory ◽  
Job Demands ◽  
University Education ◽  
Job Crafting ◽  
University Environment ◽  
The Social ◽  
The University

The first part of this article introduces the work engagement concept in a framework of the Job Demands-Resources Theory and discusses a relation between work engagement and job crafting. Next, the author presents the hypothesis that university education can form engaged employees by enhancing students’ self-efficacy beliefs about their ability to effectively crafting their future job environments. On the basis of the Social Learning Theory the author proposed three possible methods on how the university community could promote job crafting behaviors among students. These methods are: trainings and persuasions, modeling, or observation of how university top researchers work, and allowing students to experience success in changing different aspects of the university environment.

scholarly journals Social learning strategies regulate the wisdom and madness of interactive crowds

2018 ◽  
Author(s):  
Wataru Toyokawa ◽  
Andrew Whalen ◽  
Kevin N. Laland
Keyword(s):  
Social Learning ◽  
Learning Strategies ◽  
Group Size ◽  
Collective Intelligence ◽  
Collective Wisdom ◽  
The Social ◽  
Challenging Tasks ◽  
Task Uncertainty ◽  
The Individual ◽  
Social Learning Strategies

AbstractWhy groups of individuals sometimes exhibit collective ‘wisdom’ and other times maladaptive ‘herding’ is an enduring conundrum. Here we show that this apparent conflict is regulated by the social learning strategies deployed. We examined the patterns of human social learning through an interactive online experiment with 699 participants, varying both task uncertainty and group size, then used hierarchical Bayesian model-ftting to identify the individual learning strategies exhibited by participants. Challenging tasks elicit greater conformity amongst individuals, with rates of copying increasing with group size, leading to high probabilities of herding amongst large groups confronted with uncertainty. Conversely, the reduced social learning of small groups, and the greater probability that social information would be accurate for less-challenging tasks, generated ‘wisdom of the crowd’ effects in other circumstances. Our model-based approach provides evidence that the likelihood of collective intelligence versus herding can be predicted, resolving a longstanding puzzle in the literature.

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