Andrea Petrone, Paulo Borges, Fernando Pereira
et al.
The Azores Archipelago is known for its important natural heritage, yet its ecosystems face a “green tsunami” in the form of numerous exotic and invasive species. This influx has wrought serious biodiversity loss and degradation of ecosystem services, representing one of the greatest threats to conservation across the islands. Originating from accelerated global trade and travel, these invasions impact human activities, public health and economic sectors alike. The PRIBES project intends to contribute to "The Regional Strategy for the Management of Terrestrial and Freshwater Exotic and Invasive Species in the Azores" (PRIBES-LIFE-IP- Estratégia regional para o controlo e prevenção de espécies exóticas invasoras - no âmbito do projeto LIFE IP AZORES NATURA, LIFE17 IPE/PT/000010). Recently, a plan was delivered to the Azorean government that proposes as key strategy: an unified Azores Invasive Species Task Force, a central coordination unit and island‐level focal points defined clear leadership roles for agencies and stakeholders (Axis 1), while stringent pre‐export controls, quarantine measures and risk analyses blocked new arrivals (Axis 2); parallel early‐detection teams and citizen‐science networks screened ports, airports and nurseries and triggered rapid eradication protocols (Axis 3), guided by a tiered framework of eradication, containment, control and mitigation chosen on feasibility and cost–benefit grounds (Axis 4). Simultaneously, national and international partnerships with IUCN (International Union for Conservation of Nature) ISSG (Invasive Species Specialist Group), CABI (Commonwealth Agricultural Bureaux International) and other island regions fostered data exchange (Axis 5), targeted scientific research investigated invasion pathways and management efficacy (Axis 6) and a central observatory consolidated occurrence records and risk assessments (Axis 7). Meanwhile, outreach campaigns, industry training and school programmes rallied public awareness (Axis 8). The AZORES BIOPORTAL (ABP) is a regional e-infrastructure dedicated to the mobilisation, curation and dissemination of biodiversity data from the Azores. It provides centralised data repository for researchers, policy-makers and educators; validated species checklists, including endemic, native and introduced species; integration with national and international biodiversity networks, including PORBIOTA, GBIF and LifeWatch ERIC; and tools for data visualisation and access, supporting conservation, ecological research and environmental management. ABP follows the FAIR (Findable, Accessible, Interoperable, Reusable) and supports open science. Mapping the occurrence of both native (endemic and non endemic) and exotic species is of key importance for the PRIBES project and the ABP intiative.A total of 243 vascular plant taxa were recorded across São Jorge Island, encompassing 89 families. These records correspond to 4,524 individual plant occurrences, including repeated observations of the same species across different sites. As each photographic observation is tied to unique geographic coordinates, all recorded specimens represent new spatial records for the Island’s flora. Amongst the taxa, 53 are considered endemic to the Azores, 131 are introduced, 58 are native and one species (Dracaena draco (L.) L.) is of indeterminate status. These correspond to 1,773 individual occurrences of endemic taxa, 1779 introduced, 970 native and one with indeterminate status. At the family level, 31 families include endemic taxa, 63 include introduced taxa, 34 include native taxa and one family contains a taxon of indeterminate status.The inventory includes several noteworthy Azorean endemics, spanning both ferns and flowering plants. Amongst the ferns, notable records include Crisped Buckler Fern Dryopteris crispifolia Rasbach, Reichst. & Vida, Azorean Buckler Fern Dryopteris azorica (Christ) Alston and Azorean Rockcap Fern Polypodium macaronesicum subsp. azoricum (Vasc.) Rumsey, Carine & Robba. Iconic flowering species and woody endemics recorded during the survey comprise Azorean Cherry Prunus lusitanica subsp. azorica (Mouill.) Franco, Azorean Buckthorn Frangula azorica Grubov, Azorean Eyebright Euphrasia grandiflora Hochst. ex Seub., Azorean Greater-hawkbit Leontodon filii (Hochst. ex Seub.) Paiva & Ormonde and Narrow-lipped Butterfly Orchid Platanthera micrantha (Hochst. ex Seub.) Schltr. Additional endemic taxa include Azorean Dock Rumex azoricus Rech.f., Azorean Holly Ilex azorica Gand., Azorean Umbrella Milkwort Tolpis azorica (Nutt.) P. Silva and the hemiparasitic Azorean Dwarf Mistletoe Arceuthobium azoricum Wiens & Hawksw. Other significant native species recorded include the ferns Wilson's Filmy-fern Hymenophyllum wilsonii Hook., Killarney Fern Vandenboschia speciosa (Willd.) G.Kunkel and Scaly Tongue-fern Elaphoglossum hirtum (Sw.) C.Chr., Cretan Thyme Thymus caespititius Brot., Many-stalked Spike-rush Eleocharis multicaulis (Sm.) Desv. and the more common native Firetree Morella faya (Aiton) Wilbur.Amongst the most problematic surveyed exotic invasive plant species are the Ginger Lily Hedychium gardnerianum Sheppard ex Ker-Gawl., Knotweed Persicaria capitata (Buch.-Ham. ex D.Don) H.Gross, Bigleaf Hydrangea Hydrangea macrophylla (Thunb.) Ser., Crofton Weed Ageratina adenophora (Spreng.) R.M.King & H.Rob., Australian Cheesewood Pittosporum undulatum Vent. and the Wandering Jew Tradescantia fluminensis Vell., as well as the American Pokeweed Phytolacca americana L.
Julián Garrido, Susana Sánchez, Edgar Ribeiro João
et al.
The Square Kilometre Array Observatory (SKAO) faces unprecedented technological challenges due to the vast scale and complexity of its data. This paper provides an overview of research by the AMIGA group to address these computing and reproducibility challenges. We present advancements in semantic data models, analysis services integrated into federated infrastructures, and the application to astronomy studies of techniques that enhance research transparency. By showcasing these astronomy work, we demonstrate that achieving reproducible science in the Big Data era is feasible. However, we conclude that for the SKAO to succeed, the development of the SKA Regional Centre Network (SRCNet) must explicitly incorporate these reproducibility requirements into its fundamental architectural design. Embedding these standards is crucial to enable the global community to conduct verifiable and sustainable research within a federated environment.
Paula Momo Cabrera, Nicholas A. Bokulich, Petra Zimmermann
ABSTRACT The gut microbiome is crucial for host health. Early childhood is a critical period for the development of a healthy gut microbiome, but it is particularly sensitive to external influences. Recent research has focused on using advanced techniques like shotgun metagenome sequencing to identify key microbial signatures and disruptions linked to disease. For accurate microbiome analysis, samples need to be collected and stored under specific conditions to preserve microbial integrity and composition, with −80°C storage considered the gold standard for stabilization. This study investigates the effect of domestic freezer storage on the microbial composition of stool samples obtained from 20 children under 4 years of age with the use of shotgun metagenome sequencing. Fresh stool samples were aliquoted into sterile tubes, with one aliquot stored at 4°C and analyzed within 24 hours, while others were frozen in domestic freezers (below −18°C) and analyzed after 1 week, 2 months, and 6 months. Assessments of contig assembly quality, microbial diversity, and antimicrobial resistance genes revealed no significant degradation or variation in microbial composition.IMPORTANCEMost prior studies on sample storage have relied on amplicon sequencing, which is less applicable to metagenome sequencing—given considerations of contig quality and functional gene detection—and less reliable in representing microbial composition. Moreover, the effects of domestic freezer storage for at-home stool collection on microbiome profiles, contig quality, and antimicrobial resistance gene profiles have not been previously investigated. Our findings suggest that stool samples stored in domestic freezers for up to 6 months maintain the integrity of metagenomic data. These findings indicate that domestic freezer storage does not compromise the integrity or reproducibility of metagenomic data, offering a reliable and accessible alternative for temporary sample storage. This approach enhances the feasibility of large-scale at-home stool collection and citizen science projects, even those focused on the more easily perturbed early life microbiome. This advancement enables more inclusive research into the gut microbiome, enhancing our understanding of its role in human health.
Precious Makiyi, Michael Udedi, Moses Kumwenda
et al.
Abstract Background The intersection between mental health and culture is more prominent when we study how different mental health conditions present in different cultures. There is enough evidence to suggest that mental health conditions like depression, for instance, present differently in Western and non-Western societies. Most phenomenological studies on youth depression have been done in high-income countries. This systematic review, therefore, seeks to understand how depression is experienced by youths (10–24 years) and their carers in SSA. Methods Two research assistants (with the help of P. M.) shall independently search articles on the following databases: PubMed, PsycINFO, Embase, HealthSTAR, CINAHL, Google Scholar, Web of Science, and Scopus. Two reviewers will then independently evaluate the selected articles based on a systematic search strategy, extract relevant data, and synthesize findings using meta-aggregation techniques. We will use the Preferred Reporting Items of Systematic reviews and Meta-Analyses (PRISMA) guidelines in reporting results. The protocol is registered with the PROSPERO database (CRD42024556661). Discussion The results from this systematic review will help researchers especially in SSA to have a better understanding of how depression is experienced by adolescents in the region and its impact on their guardians. This has a potential of informing a diagnostic or screening tool that is sensitive to the context of SSA. Systematic review registration PROSPERO CRD42024556661. Date of registration: 10th June 2024.
Community science observational datasets are useful in epidemiology and ecology for modeling species distributions, but the heterogeneous nature of the data presents significant challenges for standardization, data quality assurance and control, and workflow management. In this paper, we present a data workflow for cleaning and harmonizing multiple community science datasets, which we implement in a case study using eBird, iNaturalist, GBIF, and other datasets to model the impact of highly pathogenic avian influenza in populations of birds in the subantarctic. We predict population sizes for several species where the demographics are not known, and we present novel estimates for potential mortality rates from HPAI for those species, based on a novel aggregated dataset of mortality rates in the subantarctic.
This course introduces life scientists to practical data science topics used in biology, such as data handling and visualisation, statistical analysis, applications of AI, and use of publicly available databases. The course provides hands-on training in tools and resources appropriate to your research, including introducing the use of Python for handling and visualising data, statistical analysis, and the application of machine learning. You will also be introduced to data science theory and practice, including best practices for undertaking analyses, data management, and reproducibility. The first iteration of the course ran in 2025. Here, we have made the course materials available for you to access at any time.
This study explores how computing science students (<i>n</i> = 335) use ChatGPT, their trust in its information, their navigation of plagiarism issues, and their confidence in addressing plagiarism and academic integrity. A mixed-methods approach was used, combining quantitative survey data with a qualitative thematic analysis of student comments to provide a comprehensive understanding of these issues. The findings reveal that ChatGPT has become integral to students’ academic routines, with 87.8% using it weekly with variable frequency. Most students (70.3%) believe the university should allow ChatGPT use, and 66.6% think it is fair to use it for academic purposes despite 57.4% distrusting its information. Additionally, 53.8% worry about accidentally plagiarising when using ChatGPT. Overall, students have moderate confidence in addressing these academic integrity issues, with no differences between undergraduate and postgraduate students. Male students reported higher confidence in handling plagiarism and academic integrity issues than female students, suggesting underlying differences in how students perceive and interact with generative AI technologies. A thematic analysis of 74 student comments on their ChatGPT experience revealed four themes: (a) Usage and Role of ChatGPT, (b) Ethical and Responsible Use, (c) Limitations and Accuracy, and (d) Impact on Education and Need for Clear Guidelines. This study contributes to the ongoing debate on accepting and using ChatGPT, highlighting the need for institutions to provide clear guidelines and ethical considerations to ensure responsible use within educational contexts.
Emerging data-driven scientific workflows are seeking to leverage distributed data sources to understand end-to-end phenomena, drive experimentation, and facilitate important decision-making. Despite the exponential growth of available digital data sources at the edge, and the ubiquity of non trivial computational power for processing this data, realizing such science workflows remains challenging. This paper explores a computing continuum that is everywhere and nowhere -- one spanning resources at the edges, in the core and in between, and providing abstractions that can be harnessed to support science. It also introduces recent research in programming abstractions that can express what data should be processed and when and where it should be processed, and autonomic middleware services that automate the discovery of resources and the orchestration of computations across these resources.
Introduction: Despite the ubiquity of statistics in numerous academic disciplines, including the life sciences, many researchers–who are not statistically trained–struggle with the correct application of statistical analysis, leading to fundamental errors in their work. The complexity and importance of statistics in scientific research necessitate a tool that empowers researchers from various backgrounds to conduct sound statistical analysis without being experts in the field. This paper introduces and evaluates the potential of OpenAI's latest API, known as the "coder interpreter," to fulfill this need. Methods: The coder interpreter API is designed to comprehend human commands, process CSV data files, and perform statistical analyses by intelligently selecting appropriate methods and libraries. Unlike traditional statistical software, this API simplifies the analysis process by requiring minimal input from the user—often just a straightforward question or command. Our work involved testing the API with actual datasets to demonstrate its capabilities, focusing on ease of use for non-statisticians and investigating its potential to improve research output, particularly in evidence-based medicine. Results: The coder interpreter API effectively utilized open-source Python libraries, renowned for their extensive resources in data science, to accurately execute statistical analyses on provided datasets. Practical examples, including a study involving diabetic patients, showcased the API's proficiency in aiding non-expert researchers in interpreting and utilizing data for their research. Discussion: Integrating AI-based tools such as OpenAI's coder interpreter API into the research process can revolutionize how scientific data is analyzed. By reducing the barrier to conducting advanced statistics, it enables researchers—including those in fields where practitioners are often concurrently medical doctors, such as in evidence-based medicine—to focus on substantive research questions. This paper highlights the potential for these tools to be adopted broadly by both novices and experts alike, thereby improving the overall quality of statistical analysis in scientific research. We advocate for the wider implementation of this technology as a step towards democratizing access to sophisticated statistical inference and data analysis capabilities.
<p style="text-align: justify;">The article is devoted to the review of national and foreign studies in professional resilience. The analyzed researches demonstrate that it is typical for foreign psychological science to consider professional resilience as a set of resources that allows a specialist in a difficult situation to provide himself with psychological well-being, which requires the skills of taking care of himself and his psychological state, providing self-help and the ability to adapt to changing conditions. The data of foreign empirical studies of professional resilience of specialists in helping professions have shown a correlation between professional resilience and emotional burnout, psychological well-being, self-compassion, and creative thinking. Also, researchers note the need for the formation of professional resilience in the educational process and labor activity. National researchers consider resilience mainly as the ability to manage functions and processes (coping, recovery) based on the internal resources of the individual, external and internal protective factors in difficult conditions in order to adapt to them and restore life satisfaction.</p>
Diego Serrano-Velasco, Diego Serrano-Velasco, Andrea Martín-Vacas
et al.
PurposeThe aim of this systematic review is to evaluate the perception of the patient, the chairside time, and the reliability and/or reproducibility of intraoral scanners for full arch in pediatric patients.MethodsA data search was performed in four databases (Medline-Pubmed, Scopus, ProQuest and Web of Science) in accordance with the PRISMA 2020 statements. Studies were classified in three categories (patient perception, scanning or impression time and reliability and/or reproducibility). The resources, the data extraction and the quality assessment were carried out independently by two operators. The variables recorded were population characteristics, material and methods aspects and included country, study design and main conclusion. A quality assessment of the selected studies was performed with QUADAS-2 tool, and Kappa-Cohen Index was calculated to analyze examiner agreement.ResultsThe initial search obtained 681 publications, and finally four studies matching inclusion criteria were selected. The distribution of the studies in the categories was three for the analysis of the patient's perception and scanning or impression time; and two items to assess the reliability and/or reproducibility of intraoral scans. All included studies have a repeated measures–transversal design. The sample size ranged between 26 and 59 children with a mean age. The intraoral scanners evaluated were Lava C.O.S, Cerec Omnicam, TRIOS Classic, TRIOS 3-Cart and TRIOS Ortho. The quality assessment of the studies using QUADAS-2 tool revealed a low risk of bias while evaluating patient perception, but an unclear risk of bias in the analysis of accuracy or chairside time. In relation to the applicability concerns, the patient selection was of high risk of bias. All studies agreed that the patient perception and comfort is better with intraoral scanners in comparison with the conventional method. The accuracy or reliability of the digital procedure is not clear, being clinically acceptable. In relation with the chairside time, it depends on the intraoral scanner, with contradictory data in the different analyzed studies.ConclusionThe use of intraoral scanners in children is a favorable option, finding a significantly higher patient perception and comfort with intraoral scanners compared to the conventional impression method. The evidence for reliability or reproducibility is not strong to date, however, the differences between the intraoral measurements and the digital models would be clinically acceptable.
The article relates to the formation of an original approach to the creation of a monitoring system for the scientific and technological sphere based on expert methods and ranking. The relevance of the topic is confirmed by the formation in the Russian Federation of a number of local monitoring subsystems that are difficult to connect with each other and do not provide in the aggregate the completeness of coverage of the scope of scientific research, development and technological work. The core element of this approach is the creation of a subsystem for monitoring scientific and technological results, evaluated by experts and organizations – recognized authorities in this field of science. The work of all other subsystems associated with the actors of scientific and technological activities, researchers, including experts, branches of science, regions of its placement, scientific journals, etc. is based on data samples presented in the central subsystem of positively evaluated scientific and technological results. The article also shows that such a system can provide not only the comparability of data from all subsystems of the R&D monitoring system, but also its completeness, transparency and resistance to voluntary and involuntary distortions. The proposed approach makes it possible to systematize attempts to digitalize the R&D sphere to ensure its full monitoring, as well as to increase the efficiency of each of its components.
Pauline Karega, Pauline Karega, David K. Mwaura
et al.
We have applied the sensitize-train-hack-community model to build awareness of and capacity in bioinformatics in Kenya. Open science is the practice of science openly and collaboratively, with tools, techniques, and data freely shared to facilitate reuse and collaboration. Open science is not a mandatory curriculum course in schools, whereas bioinformatics is relatively new in some African regions. Open science tools can significantly enhance bioinformatics, leading to increased reproducibility. However, open science and bioinformatics skills, especially blended, are still lacking among students and researchers in resource-constrained regions. We note the need to be aware of the power of open science among the bioinformatics community and a clear strategy to learn bioinformatics and open science skills for use in research. Using the OpenScienceKE framework—Sensitize, Train, Hack, Collaborate/Community—the BOSS (Bioinformatics and Open Science Skills) virtual events built awareness and empowered researchers with the skills and tools in open science and bioinformatics. Sensitization was achieved through a symposium, training through a workshop and train-the-trainer program, hack through mini-projects, community through conferences, and continuous meet-ups. In this paper, we discuss how we applied the framework during the BOSS events and highlight lessons learnt in planning and executing the events and their impact on the outcome of each phase. We evaluate the impact of the events through anonymous surveys. We show that sensitizing and empowering researchers with the skills works best when the participants apply the skills to real-world problems: project-based learning. Furthermore, we have demonstrated how to implement virtual events in resource-constrained settings by providing Internet and equipment support to participants, thus improving accessibility and diversity.
Bibliography. Library science. Information resources
Introduction While ensuring appropriate growth is essential for all children, optimising nutritional status in children with cystic fibrosis (CF) is critical for improving health outcomes. Nutritional challenges in CF are multifactorial and malnutrition is common. While gastrostomy tubes (G-tubes) can improve weight status in individuals with CF, they also have common and chronic complications resulting in clinical equipoise. To date, factors influencing G-tube decision-making among caregivers of children with CF have not been systematically explored. This review aims to chart existing knowledge about caregivers’ decisional needs related to G-tube placement, with a focus on caregivers of children with CF, as well as known medical and psychosocial benefits and risks of G-tube feedings in paediatric care.Methods and analysis This scoping review will follow the JBI methodological framework. We will include articles published between 1 January 1985 and 1 November 2023 in English and Spanish from MEDLINE (Ovid), Embase, CINAHL, PsycInfo, Cochrane Database of Systematic Reviews and Web of Science related to G-tube decision-making. Articles published in languages besides English and Spanish will be excluded. Articles will be screened for final eligibility and inclusion according to title and abstract, followed by full texts. Articles will be independently reviewed by two reviewers and any disagreements discussed with a third reviewer for consensus. We will map themes and concepts, and data extracted will be presented in tabular, diagrams and descriptive summaries.Ethics and dissemination As a form of secondary analysis, scoping reviews do not require ethics approval. This review will inform future research with caregivers involved in G-tube decision-making for children with CF. The final review will be submitted to a peer-reviewed scientific journal, disseminated at relevant academic conferences and will be shared with patients and clinicians.Trial registration number Center for Open Science. https://osf.io/g4pdb.
Nickholas Grant, Joanna L. Meyer, Michael J. Strambler
The measurement of social and emotional learning (SEL) implementation is a critical part of enhancing and understanding the effects of SEL programming. Research has shown that high-quality SEL implementation is associated with social, emotional, and academic outcomes. Schools achieve these outcomes in part through organizational practices that emphasize ongoing communication, collaboration, coordination, shared decision making, and strategic planning, processes that are ideally informed by evidence. The application of implementation science to SEL has advanced our understanding of the role of implementation in achieving student outcomes. However, the development of practical approaches for measuring and supporting SEL implementation have lagged behind work on measuring student SEL outcomes. Research-practitioner partnerships (RPP), long-term, mutually-beneficial collaborations geared toward identifying problems of practice and testing solutions for improvement, are a promising means for addressing this important gap. Though implementation science and RPPs have complementary aims, there has been limited attention to the integration of these approaches in the context of SEL programming. The goal of this paper is to offer practical strategies for measuring and using SEL implementation data in schools, using the example of an RPP that used implementation science practices to guide SEL implementation. We give special attention to structures that can support the collection and use of implementation data to improve practice, as well as considerations around developing measures, considering trade-offs of data collection decisions, and conducting data analysis.
Jared D. Willard, Charuleka Varadharajan, Xiaowei Jia
et al.
Prediction of dynamic environmental variables in unmonitored sites remains a long-standing challenge for water resources science. The majority of the world's freshwater resources have inadequate monitoring of critical environmental variables needed for management. Yet, the need to have widespread predictions of hydrological variables such as river flow and water quality has become increasingly urgent due to climate and land use change over the past decades, and their associated impacts on water resources. Modern machine learning methods increasingly outperform their process-based and empirical model counterparts for hydrologic time series prediction with their ability to extract information from large, diverse data sets. We review relevant state-of-the art applications of machine learning for streamflow, water quality, and other water resources prediction and discuss opportunities to improve the use of machine learning with emerging methods for incorporating watershed characteristics into deep learning models, transfer learning, and incorporating process knowledge into machine learning models. The analysis here suggests most prior efforts have been focused on deep learning learning frameworks built on many sites for predictions at daily time scales in the United States, but that comparisons between different classes of machine learning methods are few and inadequate. We identify several open questions for time series predictions in unmonitored sites that include incorporating dynamic inputs and site characteristics, mechanistic understanding and spatial context, and explainable AI techniques in modern machine learning frameworks.
The phrase citizen science is certainly appealing, especially for many of us who have championed the notion of increasing public engagement in science. Citizen science refers most often to projects in which non-scientists provide some of the labor needed for the collection of scientific data, often in environmental research contexts. This involvement provides volunteer workers in support of science while in turn, ideally, offering rewarding and educational participation opportunities for the volunteers. An early U.S. model for citizen participation has been the Cornell University ornithology laboratory, where the recruitment of a widely dispersed army of bird watchers and other non-scientist citizens continues to assist with bird population research and related studies.
But the specific phrase citizen science also conjures up the idea of a sort of participatory democracy operating in the service of science, allowing fresh ideas to bubble up and their policy implications to receive thoughtful attention and popular feedback early on (or, as we later learned to say, «upstream»). It might also suggest science that operates more clearly in the service of society, taking research direction from what its citizens (as community members) actually have to say. This train of thought brings citizen science closer to the idea of community-based participatory research, in which scientific goals are defined in part by communities outside of science itself. The emergence of university-based «science shops», more a European than an American phenomenon, is another close cousin in which scientists allow communities to suggest research problems that reflect community needs.
This issue of Metode presents a series of cases that illustrate both the concept and its divergent objectives: facilitating communication between scientists and non-scientists, raising public interest in science and levels of science literacy, empowering the pursuit of public policy goals, and even pushing the boundaries of social science theory. Younger participants in particular might be motivated to consider alternative career paths, potentially increasing diversity among scientific professionals. Collectively, these goals represent an ambitious agenda for the future through the advancement of frontiers in communication, education, and politics – as well as science itself. And these intriguing cases are still only a handful among many.
Who is a «citizen» and in what sense can they actually «do science»? In the early days of scientific journals, most authors were gentlemen of status. Must a citizen scientist of our own time likewise be a gentleman of status? That certainly does not seem right or fair. Yet, at the same time, the idea that «just anyone» can do science is just not quite right either. Both scientific expertise and scientific authority still matter, especially in the era of climate and COVID where misinformation is often said to be rampant – and is potentially deadly. Given that, what exactly is the role of «citizen scientists»? How do we balance the need for scientific rigor with the need for community involvement (in both directions)? This is a question with no obvious answer.
The idea of citizen science (or amateur science before it) brings with it tensions about the social nature of scientific truth, both the «citizen» part and the «science» part. As Bryan Wynne’s well-known 1989 paper on post-Chernobyl sheep farming argued, radiation scientists had one form of expertise but others (the farmers) had other forms, such as their knowledge of sheep lifecycles, seasons, pastures, and markets. Solutions to managing radiation pollution on sheep farms required both forms.
And yet scientific truth is still established by scientific consensus, not by public opinion or even public participation. In this era of «alternative facts», where it almost seems as though everyone gets to make up their own reality, assisted in no small measure by the dynamics of social media, we are regularly pushed to defend the authority of science. To do that, we need allies. I believe that one productive way of thinking about «citizen scientists» is that they are, or can become, exactly those needed allies, linking communities and societies to the fruits of scientific expertise in the form of knowledge. We should think of the role of citizen scientists not only as gathering data for the «actual» scientists to make use of, but also serving as community opinion leaders on science-related topics.
Communication. Mass media, Information resources (General)
Nadja Pernat, Jana Zscheischler, Helge Kampen
et al.
Since 2012, the citizen science project 'Mückenatlas' has been supplementing the German mosquito monitoring programme with over 28,000 submissions of physical insect samples. As the factors triggering people to catch mosquitoes for science are still unknown, we analysed the influence of mass media reports on mosquito submission numbers. Based on a theoretical framework of how mass media affect citizen responsiveness, we identified five possible influencing factors related to citizen science: (i) project awareness and knowledge, (ii) attention (economy), (iii) individual characteristics of citizen scientists and targeted communication, (iv) spatial differences and varying affectedness, and (v) media landscape. Hypotheses based on these influencing factors were quantitatively and qualitatively tested with two datasets: clipping data of mass media reports (online, television, radio and print) referring to or focussing on the 'Mückenatlas', and corresponding data of 'Mückenatlas' submissions between 2014 and 2017. In general, the number of media reports positively affected the number of mosquito submissions on a temporal and spatial scale, i.e. many media reports provoke many mosquito submissions. We found that an already heightened public and media awareness of mosquito-relevant topics combined with a direct call-to-action in a media report title led to a maximum participation. Differences on federal state level, however, suggest that factors additional to quantitative media coverage trigger participation in the 'Mückenatlas', in particular the mosquito affectedness of the resident population. Lastly, media types appear to differ in their effects on the number of submissions. Our results show under which circumstances the media presence of the 'Mückenatlas' is most effective in activating people to submit mosquito samples, and thus provide advice for designing communication strategies for citizen science projects.
Christian Bob Nicol, Emmanuel Gakuba, Gonzague Habinshuti
Seventeen years after the end of the Liberian civil war, which is partly blamed for the waning of the standard of education, the country is still grappling with providing a competency-based science educational experience that will enhance the science inquiry process skills of its youth. In this paper we used the constructivist theoretical perspective to compare the science inquiry process skills of Grade 11 students in government and private schools. The study employed a descriptive survey design and the quantitative research method. Six high schools were selected by cluster random sampling, and a total of 360 students constituted the study sample. This study found that government school students have significantly higher perceived science inquiry process skills than their private school counterparts and that an average of 42% of private school students cannot demonstrate any skills related to experimental design, data representation, communication and presentation. Male students indicated having significantly higher science inquiry process skills compared to their female counterparts. However, a varying majority across study groups practise the science inquiry process skills occasionally.