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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 informed by (a) a wider base of aggregated knowledge, (b) contributions from a diverse scientific community, (c) participatory input from stakeholders, and (d) better responsiveness to ongoing changes in the state of knowledge.

Scientific assessments, such as those by the Intergovernmental Panel on Climate Change (IPCC), inform policymakers and the public about the state of scientific evidence and related uncertainties. We studied how experts from different scientific disciplines who were authors of IPCC reports, interpret the uncertainty language recommended in the Guidance Note for Lead Authors of the IPCC Fifth Assessment Report on Consistent Treatment of Uncertainties. This IPCC guidance note discusses how to use confidence levels to describe the quality of evidence and scientific agreement, as well likelihood terms to describe the probability intervals associated with climate variables. We find that (1) physical science experts were more familiar with the IPCC guidance note than other experts, and they followed it more often; (2) experts’ confidence levels increased more with perceptions of evidence than with agreement; (3) experts’ estimated probability intervals for climate variables were wider when likelihood terms were presented with “medium confidence” rather than with “high confidence” and when seen in context of IPCC sentences rather than out of context, and were only partly in agreement with the IPCC guidance note. Our findings inform recommendations for communications about scientific evidence, assessments, and related uncertainties.

To enhance sustainability, the food system requires significant shifts in the production, processing and supply of food. Ideally, a sustainable food system should operate, not only to protect the biosphere, but also to provide nutritious, high-quality food, and to support social values, an equitable economy, and human and animal health. It should also be governed responsibly within a supportive policy environment. Implementing these shifts is a task of immense scale; but citizen participation/engagement has the potential to help make sustainability a reality through distributed learning, dynamic sensing, and knowledge generation. Technological advancements in sensing and data processing have enabled new forms of citizen participation in research. When food system research is embedded within society it can help us to understand which changes towards sustainability work and which do not. Indeed, citizen engagement in food systems research has the potential to help bring citizens on side, supporting the growth of a food culture of resilience and of sustainable practises (including dietary change). This commentary provides examples of how existing research and alternative food production systems and agroecological practises may provide possible frameworks for citizen participation in food system studies. We highlight potential future food and citizen science approaches. Widening citizen participation and encouraging the involvement of other food system actors, including those in local, national and international governance, is essential to capture the full potential of citizen science in enabling transition to a sustainable food system. For the research community citizen science offers engagement and empowerment of wider communities with science; collecting and analysing data; and creating viable solutions to food system and diet issues.

Purpose: The study aims to compare survey recruitment rates between Facebook, Twitter and Qualtrics and to assess the impact of recruitment method on estimates of energy content, food safety, carbon footprint and animal welfare across 29 foods. Design/methodology/approach: Two versions of an online survey were developed on the citizen science platform, Zooniverse. The surveys explored citizen estimations of energy density (kcal) or carbon footprint (Co2) and food safety or animal welfare of 29 commonly eaten foods. Survey recruitment was conducted via paid promotions on Twitter and Facebook and via paid respondent invites on Qualtrics. The study included approximately 500 participants (Facebook, N˜11 (ratings 358), Twitter, N˜85 (ratings 2,184), Qualtrics, N = 398 (ratings 11,910)). Kruskal–Wallis and Chi-square analyses compared citizen estimations with validated values and assessed the impact of the variables on estimations. Findings: Citizens were unable to accurately estimate carbon footprint and energy content, with most citizens overestimating values. Citizen estimates were most accurate for meat products. Qualtrics was the most successful recruitment method for the online survey. Citizen estimates between platforms were significantly different, suggesting that Facebook and Twitter may not be suitable recruitment methods for citizen online surveys. Practical implications: Qualtrics was the favourable platform for survey recruitment. However, estimates across all recruitment platforms were poor. As paid recruitment methods such as Qualtrics are costly, the authors recommend continued examination of the social media environment to develop appropriate, affordable and timely online recruitment strategies for citizen science. Originality/value: The findings indicate that citizens are unable to accurately estimate the carbon footprint and energy content of foods suggesting a focus on cons

With an increasing focus on the uptake of healthy and sustainable diets, a growing body of research has explored consumer perceptions and understanding of the environmental impacts and safety of foods. However, this body of research has used a wide range of methods to recruit participants, which can influence the results obtained. The current research explores the impact of different recruitment methods upon observed estimations of the carbon footprint (gCO2e), energy content (Kcal), food safety and animal using three different online recruitment platforms; Qualtrics (N = 397), Prolific (N = 407), Zooniverse (N~601, based on unique IP addresses). Qualtrics and Prolific participants rated the carbon footprint, energy content, food safety and animal welfare of all foods in the survey. Zooniverse citizens rated the carbon footprint or energy content then food safety or animal welfare of all foods in the survey. Kruskal-Wallis and Chi-square analyses compared the energy content and carbon footprint estimations with validated values, and differences in estimate accuracy and perceptions between recruitment methods. Participants were unable to accurately estimate the carbon footprint and energy content of foods. The carbon footprint of all foods were overestimated, with the exception of beef and lamb which was underestimated. The calorie content of fruits and vegetables are typically overestimated. Perceptions of animal welfare and food safety differed by recruitment method. Zooniverse citizens rated animal welfare standards to be lower for meat products and eggs, compared to Qualtrics and Prolific participants. Overall, Qualtrics participants typically held the highest food risk perceptions, however this varied by food type. The lack of knowledge about the carbon footprint and energy content of foods demonstrates the need for consumer education and communication to enable the move toward healthier and more sustainable diets. Perceptions of food safety and an

There is a food knowledge disconnect between the food research community, and the general population. Food experts know detailed information about foods, but there is a lack of understanding about what citizens know. Citizen science has been used successfully in various fields however, is virtually absent from food research. This pilot study explores the efficacy of Zooniverse citizen science platform as a method of food citizen research, and assesses the impact of response method, food type, portion size and weight information, on estimates of carbon footprint and energy content. Estimates of the carbon footprint (grams of carbon dioxide equivalent) and energy content (Kcal) of 10 foods were measured in a 3 (Between: Response Method; multiple-choice, slider, text box) × 3 (Within: portion size; small, medium, large) × 2 (Between: weight information; present, absent) observational survey. Citizens (N = ~516, unique IP addresses) were recruited via informal email networks. Kruskal–Wallis and Chi-square analyses compared citizen estimations with validated values, and assessed the impact of the variables on estimations. The majority of carbon footprint and energy content estimates were inaccurate, with citizens typically overestimating values. We observe an unexpected correlation between carbon footprint and energy content estimates. Portion size impacts perceptions, with estimations increasing with larger portion sizes. Weight information impacts perceptions, with estimations of carbon footprint being lower, and estimates of energy content being higher when weight information is present. Input method significantly affects observed values, estimates of carbon footprint and energy content estimates were lowest using the text box, followed by the slider tool, highest estimates were given using multiple choice. Citizens are unable to accurately estimate the carbon footprint and energy content of foods, though citizens may possess understanding of the hierarchy of v

To enhance sustainability, the food system requires significant shifts in the production, processing and supply of food. Ideally, a sustainable food system should operate, not only to protect the biosphere, but also to provide nutritious, high-quality food, and to support social values, an equitable economy, and human and animal health. It should also be governed responsibly within a supportive policy environment. Implementing these shifts is a task of immense scale; but citizen participation/engagement has the potential to help make sustainability a reality through distributed learning, dynamic sensing, and knowledge generation. Technological advancements in sensing and data processing have enabled new forms of citizen participation in research. When food system research is embedded within society it can help us to understand which changes towards sustainability work and which do not. Indeed, citizen engagement in food systems research has the potential to help bring citizens on side, supporting the growth of a food culture of resilience and of sustainable practises (including dietary change). This commentary provides examples of how existing research and alternative food production systems and agroecological practises may provide possible frameworks for citizen participation in food system studies. We highlight potential future food and citizen science approaches. Widening citizen participation and encouraging the involvement of other food system actors, including those in local, national and international governance, is essential to capture the full potential of citizen science in enabling transition to a sustainable food system. For the research community citizen science offers engagement and empowerment of wider communities with science; collecting and analysing data; and creating viable solutions to food system and diet issues.

Purpose: The study aims to compare survey recruitment rates between Facebook, Twitter and Qualtrics and to assess the impact of recruitment method on estimates of energy content, food safety, carbon footprint and animal welfare across 29 foods. Design/methodology/approach: Two versions of an online survey were developed on the citizen science platform, Zooniverse. The surveys explored citizen estimations of energy density (kcal) or carbon footprint (Co2) and food safety or animal welfare of 29 commonly eaten foods. Survey recruitment was conducted via paid promotions on Twitter and Facebook and via paid respondent invites on Qualtrics. The study included approximately 500 participants (Facebook, N˜11 (ratings 358), Twitter, N˜85 (ratings 2,184), Qualtrics, N = 398 (ratings 11,910)). Kruskal–Wallis and Chi-square analyses compared citizen estimations with validated values and assessed the impact of the variables on estimations. Findings: Citizens were unable to accurately estimate carbon footprint and energy content, with most citizens overestimating values. Citizen estimates were most accurate for meat products. Qualtrics was the most successful recruitment method for the online survey. Citizen estimates between platforms were significantly different, suggesting that Facebook and Twitter may not be suitable recruitment methods for citizen online surveys. Practical implications: Qualtrics was the favourable platform for survey recruitment. However, estimates across all recruitment platforms were poor. As paid recruitment methods such as Qualtrics are costly, the authors recommend continued examination of the social media environment to develop appropriate, affordable and timely online recruitment strategies for citizen science. Originality/value: The findings indicate that citizens are unable to accurately estimate the carbon footprint and energy content of foods suggesting a focus on cons

With an increasing focus on the uptake of healthy and sustainable diets, a growing body of research has explored consumer perceptions and understanding of the environmental impacts and safety of foods. However, this body of research has used a wide range of methods to recruit participants, which can influence the results obtained. The current research explores the impact of different recruitment methods upon observed estimations of the carbon footprint (gCO2e), energy content (Kcal), food safety and animal using three different online recruitment platforms; Qualtrics (N = 397), Prolific (N = 407), Zooniverse (N~601, based on unique IP addresses). Qualtrics and Prolific participants rated the carbon footprint, energy content, food safety and animal welfare of all foods in the survey. Zooniverse citizens rated the carbon footprint or energy content then food safety or animal welfare of all foods in the survey. Kruskal-Wallis and Chi-square analyses compared the energy content and carbon footprint estimations with validated values, and differences in estimate accuracy and perceptions between recruitment methods. Participants were unable to accurately estimate the carbon footprint and energy content of foods. The carbon footprint of all foods were overestimated, with the exception of beef and lamb which was underestimated. The calorie content of fruits and vegetables are typically overestimated. Perceptions of animal welfare and food safety differed by recruitment method. Zooniverse citizens rated animal welfare standards to be lower for meat products and eggs, compared to Qualtrics and Prolific participants. Overall, Qualtrics participants typically held the highest food risk perceptions, however this varied by food type. The lack of knowledge about the carbon footprint and energy content of foods demonstrates the need for consumer education and communication to enable the move toward healthier and more sustainable diets. Perceptions of food safety and an

There is a food knowledge disconnect between the food research community, and the general population. Food experts know detailed information about foods, but there is a lack of understanding about what citizens know. Citizen science has been used successfully in various fields however, is virtually absent from food research. This pilot study explores the efficacy of Zooniverse citizen science platform as a method of food citizen research, and assesses the impact of response method, food type, portion size and weight information, on estimates of carbon footprint and energy content. Estimates of the carbon footprint (grams of carbon dioxide equivalent) and energy content (Kcal) of 10 foods were measured in a 3 (Between: Response Method; multiple-choice, slider, text box) × 3 (Within: portion size; small, medium, large) × 2 (Between: weight information; present, absent) observational survey. Citizens (N = ~516, unique IP addresses) were recruited via informal email networks. Kruskal–Wallis and Chi-square analyses compared citizen estimations with validated values, and assessed the impact of the variables on estimations. The majority of carbon footprint and energy content estimates were inaccurate, with citizens typically overestimating values. We observe an unexpected correlation between carbon footprint and energy content estimates. Portion size impacts perceptions, with estimations increasing with larger portion sizes. Weight information impacts perceptions, with estimations of carbon footprint being lower, and estimates of energy content being higher when weight information is present. Input method significantly affects observed values, estimates of carbon footprint and energy content estimates were lowest using the text box, followed by the slider tool, highest estimates were given using multiple choice. Citizens are unable to accurately estimate the carbon footprint and energy content of foods, though citizens may possess understanding of the hierarchy of v