Geoscientists' views about science communication: predicting willingness to communicate geoscience
CecÃ­lia Costa e Silva Diamantino Insua
https://www.geoscience-communication.net/favicon_copernicus_16x16_.ico
4.2âFactors explaining the intensity of this public engagement

To answer RS 2, we used the approach of the multinomial logistic analysis model that allows the selection of predictors that, together, have a significant effect on the dependent variable intensity of communication.

Participants were asked how many science communication activities they had carried out in the previous year. Since no prior detailed explanation of âscience communication activitiesâ was given, each respondent reported the activities that they assumed as such and which they consciously carry out as science communication.

The frequency/intensity variable was then organised into three categories: âinactiveâ communicators, who reported not having carried out any activity in the last year (11.5â%), âactiveâ communicators, who performed between one and three activities (35.3â%) and âvery activeâ communicators, who reported more than four activities in the last year (53.2â%). The reference class is âvery activeâ.

The multinomial logistic analysis began with the selection of important predictor variables using several selection feature techniques, including step-by-step forward and backward techniques based on the log likelihood of models. Among all possible predictors, the best model (in terms of goodness of fit, based on the model's log likelihood) includes the following predictors: area of expertise, professional experience, institutional attitude, lack of financial support and personal satisfaction.

The goodness-of-fitÂ indicator of Nagelkerke's R2 value is 0.597. The confusion matrix (TableÂ 2) shows that the overall percentage of correct ratings is 72.4â%. Regarding the percentage of correct classifications, by category, the highest (85.5â%) is obtained in the very active category and the lowest in the inactive category (55.6â%). It is possible to conclude that the model has a good predictive ability. The table of coefficients is available in âMaterial Bâ of the Supplement.

When comparing inactive with very active (more than four activities), results show that the probability of not engaging in any communication increases significantly in individuals with 5 to 10Â years of experience compared to those with more than 20Â years. The probability of engaging in public activities increases significantly in those whose institution appreciates their efforts. Therefore, if the institution values public engagement, the probability that an individual will not engage in any communication decreases. For respondents with unsatisfactory experiences with public engagement, the probability of not engaging in any communication increases. For geoscientists from areas of expertise like geological and energy resources, the probability of engaging in activities increases.

Taking the category of very active as a reference, it is possible to conclude that the risk factors, i.e. increasing the probability of being inactive, are individuals with 5â10Â years of experience and with unsatisfactory communication experiences. On the other hand, the probability of being active (performing between one to three activities) increases for individuals whose institution moderately or highly appreciates their efforts. The probability decreases for individuals with less than 5Â years of experience and for those who do not see lack of financial support as an obstacle

Therefore, it is possible to conclude that having more than 20Â years of experience, being part of an institution who recognises efforts in public engagement and working in geological and energy resources areas foster the increase in the number of communication activities per year, while previous unsatisfactory communication experiences are a risk factor.

For the RS 2 (What explains geoscientists' public engagement?), we identified the following factors: the intensity of geoscientists' public engagement may be explained by the area of expertise, professional experience, institutional attitude, lack of financial support and personal satisfaction.

Geoscientists from areas of expertise like geological and energy resources, external geodynamics and palaeontology, geoconservation and geotourism are more likely to be active or very active in communication activities than those from areas such as history and education or environmental geology and environment and engineering geology. On the other hand, the lack of financial support and the few years of experience are factors that may induce low frequency of science communication activities.

Despite the fact that, nowadays, scientific institutions seem to be more aware of the importance of public engagement, promoting and supporting initiatives and involving scientists, funding and career progressions still depend on research rankings. Many geoscientific institutions in Portugal promote the participation of their professionals in events such as open days, European Researchers Night, Living Science Summer and at the school. Also, the funding of research projects requires work packages on the dissemination of results and outreach. However, all these endeavours are not considered in formal performance evaluation. Besides encouragement and financial resources, geoscientists could feel more committed to communicate with the public with formal recognition, logistical support, dedicated time and training.

On the other hand, we also concluded that less experienced professionals tend to engage less with the public. These results can be explained with the same argument of research rankings and lack of time, more crucial in early carriers. Moreover, the lack of public communication experience may deter geoscientists. Senior scientists with longer carriers, more recognised experience and visibility may also receive more demands.

As proved for other communities, we concluded that geoscientists with previous unsatisfactory experiences tend to communicate less. Lack of training, lack of support, non-expected impacts or so many other reasons can explain the dissatisfaction. This research focuses on scientists rather than audiences, so we can only make conclusions about the intensity of public engagement and not about quality or impact of communication. A solution to overcome this barrier would be to follow these professionals more closely, understand their difficulties and support them in overcoming them.

Regarding the area of expertise, despite dealing with complex and abstract processes and timescales, scientists from areas such external geodynamics and palaeontology tend to communicate more. Fossils (including dinosaurs) and landscapes may be difficult to understand but can be more appealing for non-expert audiences.

Geoconservation and geotourism experts work with geological heritage, an appealing topic and usually have public communication included in their duties. Some of them work in institutions like museums, science centres or geoparks and tend to be more motivated. Geological and energy resources are topics that currently receive high media visibility and social debates demanding geoscientists to engage more with public.

History and education experts seem to engage less, probably because these areas are extremely applied.

Finally, geoscientists from areas such environmental geology and environment and engineering geology tend to communicate less. This result could not have been expected, as these areas include topics such as climate change, soil and water contamination and topics with great social impact on people's health and life. On the other hand, these areas have great visibility in media and public debate, discussions are very polarised and politicised and very often geoscientist face uncomfortable experiences. These results show that communication attitudes also depend on the area of expertise. Interventions to foster public engagement among geoscientists should be targeted to different areas of expertise. Areas with more public visibility and polarisation could benefit from targeted training, addressing the specific challenges they face and working together with social and human scientists. Training for geoscience graduation students, designed to answer specific challenges such as risk and emergency response, proved to be very effective improving communication skills (Dohaney et al., 2015).

Regarding the limitations of this experimental design, the sample selected may not be representative of the population being studied. Another limitation is the issue of imbalanced samples, as the distribution of the independent variable is not equal in each group of the experiment.

With regard to the method's limitations, the small sample size needs to be considered. The multinomial logistic regression model requires a relatively large sample size in order to achieve accurate and stable estimates, particularly when there are multiple categories and many independent variables. The limited prediction accuracy is another limitation, since the multinomial logistic regression model may not always provide accurate predictions, especially when the relationships between the variables are complex and non-linear. Multinomial logistic regression is designed for categorical dependent variables and it assumes that the categories are nominal and have no inherent order or ranking.