scholarly journals Estimating the reproducibility of social learning research published between 1955 and 2018

2021 ◽  
Vol 8 (9) ◽  
pp. 210450
Author(s):  
Riana Minocher ◽  
Silke Atmaca ◽  
Claudia Bavero ◽  
Richard McElreath ◽  
Bret Beheim
Keyword(s):  
Social Learning ◽  
Research Topic ◽  
Data Recovery ◽  
Data Availability ◽  
Behavioural Ecology ◽  
The Social ◽  
Sample Data ◽  
Direct Data ◽  
Learning Research ◽  
Behavioural Sciences

Reproducibility is integral to science, but difficult to achieve. Previous research has quantified low rates of data availability and results reproducibility across the biological and behavioural sciences. Here, we surveyed 560 empirical publications, published between 1955 and 2018 in the social learning literature, a research topic that spans animal behaviour, behavioural ecology, cultural evolution and evolutionary psychology. Data were recoverable online or through direct data requests for 30% of this sample. Data recovery declines exponentially with time since publication, halving every 6 years, and up to every 9 years for human experimental data. When data for a publication can be recovered, we estimate a high probability of subsequent data usability (87%), analytical clarity (97%) and agreement of published results with reproduced findings (96%). This corresponds to an overall rate of recovering data and reproducing results of 23%, largely driven by the unavailability or incompleteness of data. We thus outline clear measures to improve the reproducibility of research on the ecology and evolution of social behaviour.

scholarly journals Reproducibility improves exponentially over 63 years of social learning research

2020 ◽  
Author(s):  
Riana Minocher ◽  
Silke Atmaca ◽  
Claudia Bavero ◽  
Richard McElreath ◽  
Bret Beheim
Keyword(s):  
Social Learning ◽  
Cultural Evolution ◽  
High Probability ◽  
Research Topic ◽  
Data Recovery ◽  
Behavioural Ecology ◽  
The Social ◽  
Direct Data ◽  
Learning Research ◽  
Data Usability

Reproducibility is integral to science, but difficult to achieve. We surveyed 560 empirical publications, published between 1955 and 2018 in the social learning literature, a research topic that spans animal behaviour, behavioural ecology, cultural evolution, and evolutionary psychology. Data was recoverable online or through direct data requests for 30% of this sample. Moreover, data recovery declines exponentially with time since publication, halving every 6 years, and up to every 9 years for human experimental data. When data for a publication can be recovered, we estimate a high probability of subsequent data usability (87%), analytical clarity (97%), and agreement of published results with reproduced findings (96%). This corresponds to an overall rate of recovering data and reproducing results of 23%, largely driven by unavailability or incompleteness of data. We thus outline clear measures to improve reproducibility of research on the ecology and evolution of social behaviour.

Performance Comparison among Meta Classifier Algorithms in WEKA

2019 ◽  
Vol 1 (2) ◽  
pp. 106-112
Author(s):  
Nur Amiratun Nazihah Roslan ◽  
Hairulnizam Mahdin ◽  
Shahreen Kasim
Keyword(s):  
Social Networking ◽  
Performance Comparison ◽  
Data Availability ◽  
Data Mining Tool ◽  
Huge Data ◽  
Technology Advancement ◽  
The Social ◽  
The World ◽  
Media Platform ◽  
Mining Tool

With the rise of social networking approach, there has been a surge of users generated content all over the world and with that in an era where technology advancement are up to the level where it could put us in a step ahead of pathogens and germination of diseases, we couldn’t help but to take advantage of that advancement and provide an early precaution measures to overcome it. Twitter on the other hand are one of the social media platform that provides access towards a huge data availability. To manipulate those data and transform it into an important information that could be used in many different scope that could help improve people’s life for the better. In this paper, we gather all algorithm that are available inside Meta Classifier to compare between them on which algorithm suited the most with the dengue fever dataset. This research are using WEKA as the data mining tool for data analyzation.

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 Role of Images on Illness Behaviour: Interdisciplinary Theory, Evidence, and Ideas

2020 ◽  
pp. 003329412094560
Author(s):  
Jennifer Murray ◽  
Brian Williams
Keyword(s):  
Health Outcomes ◽  
Health Beliefs ◽  
Intervention Development ◽  
Current Paper ◽  
Illness Experience ◽  
Illness Behaviour ◽  
The Social ◽  
Image Representations ◽  
Behavioural Sciences

If illness behaviour is to be fully understood, the social and behavioural sciences must work together to understand the wider forms in which illness is experienced and communicated with individuals and society. The current paper synthesised literature across social and behavioural sciences exploring illness experience and communication through physical and mental images. It argues that images may have the capacity to embody and influence beliefs, emotions, and health outcomes. While four commonalities exist, facilitating understandings of illness behaviour across the fields (i.e., understanding the importance of the patient perspective; perception of the cause, sense of identity with the illness, consequences, and level of control; health beliefs influencing illness experience, behaviours, and outcomes; and understanding illness beliefs and experiences through an almost exclusive focus on the written or spoken word), we will focus on exploring the fourth commonality. The choice to focus on the role of images on illness behaviour is due to the proliferation of interventions using image-based approaches. While these novel approaches show merit, there is a scarcity of theoretical underpinnings and explorations into the ways in which these are developed and into how people perceive and understand their own illnesses using image representations. The current paper identified that the use of images can elucidate patient and practitioner understandings of illness, facilitate communication, and potentially influence illness behaviours. It further identified commonalities across the social and behavioural sciences to facilitate theory informed understandings of illness behaviour which could be applied to visual intervention development to improve health outcomes.

CAUSES OF ADULT ILLITERACY: A CASE STUDY OF FEROZEPUR DISTRICT

2016 ◽  
pp. 86-96
Author(s):  
Kulwinder Singh ◽  
Ravinder Kamboj
Keyword(s):  
Physical Punishment ◽  
Early Marriage ◽  
Low Literacy ◽  
Interview Schedule ◽  
Literacy Rate ◽  
The Social ◽  
Sample Data ◽  
Literacy Process ◽  
Social Causes

Present research is an attempt to study the social, educational and personal causes of adult illiteracy. Qualitative approach was adopted to evaluate causes of illiteracy. Ferozepur district of Punjab (India) was chosen as the region for conducting this study mainly for its low literacy rate and being a border area of Punjab, from where 60 adult respondents were taken as sample. Data was collected by a self-administered interview schedule, which seeks information regarding causes of non-educability. Findings of the study show that lack of parents interest, alcoholism/drug abuse of father and 'early marriage' have been reported as social causes for illiteracy among adults while in educational causes, adult respondents have enlisted three main causes 'school was far away', 'physical punishment' and 'behaviour of teacher not being appropriate'. Poor economic conditions, no source of income, over workload, hesitation and over-aging emerged as personal causes for discontinuation of the literacy process. It has been suggested that intervention programmes should be introduced in border areas to increase participation in adult education programmes and to remove obstacles in getting education.

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.

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