Matthew S Nurse
Biographic Data
| ID | 4258226 |
|---|---|
| NAME | Matthew S Nurse |
| GIVEN NAMES | Matthew S |
| FAMILY NAME | Nurse |
| SIGNATURE | NURSE M S |
| AFFILIATIONS | Australian National University, Canberra, Australia |
| ORCID | 0000-0003-1787-5914 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 1 |
Science Communication as a Collective Intelligence Endeavor: A Manifesto and Examples for Implementation
Effective science communication is challenging when scientific messages are informed by a continually updating evidence base and must often compete against misinformation. We argue that we need a new program of science communication as collective intelligence—a collaborative approach, supported by technology. This would have four key advantages over the typical model where scientists communicate as individuals: scientific messages would be inform…
National identity predicts public health support during a global pandemic
Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1, N = 49,968 across 67 countries), we investigated self-reported factors associated with public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions (e.g., closing bars and restaurants) during …
Predicting attitudinal and behavioral responses to Covid-19 pandemic using machine learning
At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multi-national data collected by the International Collaboration on the Social…
I’ll See It When I Believe It: Motivated Numeracy in Perceptions of Climate Change Risk
People’s attitudes about Anthropogenic Climate Change (ACC) risks are not only influenced by scientific data, such as the likelihood of harm, the consequences of failing to act and the cost and effectiveness of mitigation. Instead, when people receive information about controversial topics of decision-relevant science like ACC they often defer to their political attitudes. Recent research has shown that more numerate people can be more polarized …
Science Communication as a Collective Intelligence Endeavor: A Manifesto and Examples for Implementation
Effective science communication is challenging when scientific messages are informed by a continually updating evidence base and must often compete against misinformation. We argue that we need a new program of science communication as collective intelligence—a collaborative approach, supported by technology. This would have four key advantages over the typical model where scientists communicate as individuals: scientific messages would be inform…
I’ll See It When I Believe It: Motivated Numeracy in Perceptions of Climate Change Risk
People’s attitudes about Anthropogenic Climate Change (ACC) risks are not only influenced by scientific data, such as the likelihood of harm, the consequences of failing to act and the cost and effectiveness of mitigation. Instead, when people receive information about controversial topics of decision-relevant science like ACC they often defer to their political attitudes. Recent research has shown that more numerate people can be more polarized …
National identity predicts public health support during a global pandemic
Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1, N = 49,968 across 67 countries), we investigated self-reported factors associated with public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions (e.g., closing bars and restaurants) during …
Predicting attitudinal and behavioral responses to Covid-19 pandemic using machine learning
At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multi-national data collected by the International Collaboration on the Social…
Science Communication as a Collective Intelligence Endeavor: A Manifesto and Examples for Implementation
Effective science communication is challenging when scientific messages are informed by a continually updating evidence base and must often compete against misinformation. We argue that we need a new program of science communication as collective intelligence—a collaborative approach, supported by technology. This would have four key advantages over the typical model where scientists communicate as individuals: scientific messages would be inform…
Computer Science (3 works) · Medicine (3 works) · Political science (3 works) · 2019-20 coronavirus outbreak (2 works) · Climate Change Communication and Perception (2 works) · COVID-19 and Mental Health (2 works) · COVID-19 epidemiological studies (2 works) · Data science (2 works) · Pandemic (2 works) · Psychology (2 works)