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30 results for “policymaking”
IPBES Assessment of the diverse values and valuation of nature - Figures presented in the summary for policymakers
<p>These figures are an integral part of the Summary for policymakers of the Methodological assessment of the diverse values and valuation of nature of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. To see the full document visit the related links. </p>
Dataset for 'A Matter of Culture? Conceptualising and Investigating 'Evidence Cultures' within Research on Evidence-Informed Policymaking'
<p><strong><span>Introduction</span></strong><strong><span><br></span></strong><span>This document describes the data collection and datasets used in the manuscript "A Matter of Culture? Conceptualising and Investigating ‘Evidence Cultures’ within Research on Evidence-Informed Policymaking" <span>[1].</span></span></p> <p><strong><span>Data Collection</span></strong></p> <p><span>To construct the citation network analysed in the manuscript, we first designed a series of queries to capture a large sample of literature exploring the relationship between evidence, policy, and culture from various perspectives. Our team of domain experts developed the following queries based on terms common in the literature. These queries search for the terms included in the titles, abstracts, and associated keywords of WoS indexed records (i.e. ‘TS=’). While these are separated below for ease of reading, they combined into a single query via the OR operator in our search. Our search was conducted on the Web of Science’s (WoS) Core Collection through the University of Edinburgh Library subscription on 29/11/2023, returning a total of <strong><u>2,089 records</u></strong>.</span></p> <p><em><span>TS = ((“cultures of evidence” OR “culture of evidence” OR “culture of knowledge” OR “cultures of knowledge” OR “research culture” OR “research cultures” OR “culture of research” OR “cultures of research” OR “epistemic culture” OR “epistemic cultures” OR “epistemic community” OR “epistemic communities” OR “epistemic infrastructure” OR “evaluation culture” OR “evaluation cultures” OR “culture of evaluation” OR “cultures of evaluation” OR “thought style” OR “thought styles” OR “thought collective” OR “thought collectives” OR “knowledge regime” OR “knowledge regimes” OR “knowledge system” OR “knowledge systems” OR “civic epistemology” OR “civic epistemologies”) AND (“policy” OR “policies” OR “policymaking” OR “policy making” OR “policymaker” OR “policymakers” OR “policy maker” OR “policy makers” OR “policy decision” OR “policy decisions” OR “political decision” OR “political decisions” OR “political decision making”))</span></em></p> <p><em><span>OR</span></em></p> <p><em><span>TS = ((“culture” OR “cultures”) AND ((“evidence-based” OR “evidence-informed” OR “evidence-led” OR “science-based” OR “science-informed” OR “science-led” OR “research-based” OR “research-informed” OR “evidence use” OR “evidence user” OR “evidence utilisation” OR “evidence utilization” OR “research use” OR “researcher user” OR “research utilisation” OR “research utilization” OR “research in” OR “evidence in” OR “science in”) NEAR/1 (“policymaking” OR “policy making” OR “policy maker” OR “policy makers”)))</span></em></p> <p><em><span>OR</span></em></p> <p><em><span>TS = ((“culture” OR “cultures”) AND (“scientific advice” OR “technical advice” OR “scientific expertise” OR “technical expertise” OR “expert advice”) AND (“policy” OR “policies” OR “policymaking” OR “policy making” OR “policymaker” OR “policymakers” OR “policy maker” OR “policy makers” OR “political decision” OR “political decisions” OR “political decision making”))<span> </span></span></em></p> <p><em><span>OR</span></em></p> <p><em><span>TS = ((“culture” OR “cultures”) AND (“post-normal science” OR “trans-science” OR “transdisciplinary” OR “transdisiplinarity” OR “science-policy interface” OR “policy sciences” OR “sociology of knowledge” OR “sociology of science” OR “knowledge transfer” OR “knowledge translation” OR “knowledge broker” OR “implementation science” OR “risk society”) AND (“policymaking” OR “policy making” OR “policymaker” OR “policymakers” OR “policy maker” OR “policy makers”))</span></em></p> <p><strong><span>Citation Network Construction</span></strong></p> <p><span>All bibliographic metadata on these 2,089 records were downloaded in five batches in plain text and then merged in R. We then parsed these data into network readable files. All unique reference strings are given unique node IDs. A node-attribute-list (‘CE_Node’) links identifying information of each document with its node ID, including authors, title, year of publication, journal WoS ID, and WoS citations. An edge-list (‘CE_Edge’) records all citations from these documents to their bibliographies – with edges going <em>from</em> a citing document <em>to</em> the cited – using the relevant node IDs. These data were then cleaned by (a) matching DOIs for reference strings that differ but point to the same paper, and (b) manual merging of obvious duplicates caused by referencing errors.</span></p> <p><span>Our initial dataset consisted of 2,089 <em>retrieved</em> documents and 123,772 <em>unretrieved</em> cited documents (i.e. documents that were cited within the publications we retrieved but which were not one of these 2,089 documents). These documents were connected by 157,229 citation links, but ~87% of the documents in the network were cited just once. To focus on relevant literature, we filtered the network to include <em>only</em> documents with at least three citation or reference links. We further refined the dataset by focusing on the main connected component, resulting in 6,650 nodes and 29,198 edges. <strong><u>It is this dataset that we publish here</u></strong>, and it is this network that underpins Figure 1, Table 1, and the qualitative examination of documents (see manuscript for further details). </span></p> <p><span>Our final network dataset contains 1,819 of the documents in our original query (~87% of the original retrieved records), and 4,831 documents not retrieved via our Web of Science search but cited by at least three of the retrieved documents. We then clustered this network by modularity maximization via the Leiden algorithm <span>[2]</span>, detecting 14 clusters with Q=0.59. Citations to documents within the same cluster constitute ~77% of all citations in the network. </span></p> <p><strong><span>Citation Network Dataset Description</span></strong></p> <p><span>We include two network datasets: (i) ‘CE_Node.csv’ that contains 1,819 retrieved documents, 4,831 unretrieved referenced documents, making for a total of 6,650 documents (nodes); (ii)’CE_Edge.csv’ that records citations (edges) between the documents (nodes), including a total of 29,198 citation links. These files can be used to construct a network with many different tools, but we have formatted these to be used in Gephi 0.10<span>[3]</span>. </span></p> <p><strong><span>‘CE_Node.csv’</span></strong><span> is a comma-separate values file that contains two types of nodes: </span></p> <p><span><span>i.<span> </span></span></span><span>Retrieved documents – these are documents captured by our query. These include full bibliographic metadata and reference lists. </span></p> <p><span><span>ii.<span> </span></span></span><span>Non-retrieved documents – these are documents referenced by our retrieved documents but were not retrieved via our query. These only have data contained within their reference string (i.e. first author, journal or book title, year of publication, and possibly DOI). </span></p> <p><span>The columns in the .csv refer to:</span></p> <p><span><span>-<span> </span></span></span><em><span>Id</span></em><span>, the node ID</span></p> <p><span><span>-<span> </span></span></span><em><span>Label</span></em><span>, the reference string of the document</span></p> <p><span><span>-<span> </span></span></span><em><span>DOI</span></em><span>, the DOI for the document, if available</span></p> <p><span><span>-<span> </span></span></span><em><span>WOS_ID</span></em><span>, WoS accession number</span></p> <p><span><span>-<span> </span></span></span><em><span>Authors</span></em><span>, named authors</span></p> <p><span><span>-<span> </span></span></span><em><span>Title</span></em><span>, title of document</span></p> <p><span><span>-<span> </span></span></span><em><span>Document_type</span></em><span>, variable indicating whether a document is an article, review, etc.</span></p> <p><span><span>-<span> </span></span></span><em><span>Journal_book_title, </span></em><span>journal of publication or title of book</span></p> <p><span><span>-<span> </span></span></span><em><span>Publication year</span></em><span>, year of publication.</span></p> <p><span><span>-<span> </span></span></span><em><span>WOS_times_cited</span></em><span>, total Core Collection citations as of 29/11/2023</span></p> <p><span><span>-<span> </span></span></span><em><span>Indegree</span></em><span>, number of <strong><em>within</em></strong> network citations to a given document</span></p> <p><span><span>-<span> </span></span></span><em><span>Cluster</span></em><span>, provides the cluster membership number as discussed in the manuscript (Figure 1)</span></p> <p><strong><span>‘CE_Edge.csv’</span></strong><span> is a comma-separated values file that contains edges (citation links) between nodes (documents) (<em>n</em>=29,198). The columns refer to:</span></p> <p><span><span>-<span> </span></span></span><em><span>Source</span></em><span>, node ID of the <em>citing</em> document</span></p> <p><span><span>-<span> </span></span></span><em><span>Target, </span></em><span>node ID of the <em>cited</em> document</span></p> <p><strong><span>Cluster Analysis</span></strong></p> <p><span>We qualitatively analyse a set of publications from seven of the largest clusters in our manuscript. For this, we calculated the within cluster indegree of nodes, and read through the 10 most cited retrieved documents and 10 most cited unretrieved documents. To generate these lists, sub-graphs for each cluster needed to be generated, and then indegree was measured (i.e. counting the number of citations from papers within a cluster to other papers in that same cluster).</span></p> <p><strong><span>Notes</span></strong></p> <p><a href="https://zenodo.org/records/6615221#_ftnref1"><span>[1]</span></a><span> Bandola-Gill, J., Andersen, N., Leng, R. I., Pattyn, V., & Smith, K. E. (forthcoming). A Matter of Culture? Conceptualising and Investigating ‘Evidence Cultures’ within Research on Evidence-Informed Policymaking. Policy and Society</span></p> <p><a href="https://zenodo.org/records/6615221#_ftnref6"><span>[2]</span></a><span> Traag, V. A., Waltman, L., & van Eck, N. J. (2019). From Louvain to Leiden: guaranteeing well-connected communities. Scientific reports, 9(1), 5233. </span><a href="https://doi.org/10.1038/s41598-019-41695-z"><span>https://doi.org/10.1038/s41598-019-41695-z</span></a></p> <p><a href="https://zenodo.org/records/6615221#_ftnref5"><span>[3]</span></a><span> Bastian, M., Heymann, S., & Jacomy, M. (2009). Gephi: an open source software for exploring and manipulating networks. International AAAI Conference on Weblogs and Social Media. Gephi is available via </span><a href="https://gephi.org/"><span>https://gephi.org/</span></a></p> <p><span> </span></p>
IPBES Invasive Alien Species Assessment: Summary for Policymakers. Figures, tables and captions
<p>Figures, tables and their captions from the Summary for Policymakers of the Thematic Assessment Report on Invasive Alien Species and their Control of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services.</p>
IPBES Invasive Alien Species Assessment: Summary for Policymakers. Figures, tables and captions in Arabic
<p>Arabic translations of the figures, tables and their captions from the Summary for Policymakers of the Thematic Assessment Report on Invasive Alien Species and their Control of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services.</p>
IPBES Invasive Alien Species Assessment: Summary for Policymakers. Figures, tables and captions in Chinese
<p>Chinese translations of the figures, tables and their captions from the Summary for Policymakers of the Thematic Assessment Report on Invasive Alien Species and their Control of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services.</p>
IPBES Invasive Alien Species Assessment: Summary for Policymakers. Figures, tables and captions in French
<p>French translations of the figures, tables and their captions from the Summary for Policymakers of the Thematic Assessment Report on Invasive Alien Species and their Control of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services.</p>
IPBES Invasive Alien Species Assessment: Summary for Policymakers. Figures, tables and captions in Russian
<p>Russian translations of the figures, tables and their captions from the Summary for Policymakers of the Thematic Assessment Report on Invasive Alien Species and their Control of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services.</p>
Summary for policymakers of the assessment report on land degradation and restoration of the Intergovernmental SciencePolicy Platform on Biodiversity and Ecosystem Services: Figure SPM.1
<p>The purpose of Figure SPM.1 is to support the statement that land degradation occurs just about everywhere in the world (i.e. it is ‘pervasive’), takes many forms, and that examples of successful restoration are also widespread. The figure consists of a backdrop map of the world from a multiple land degradation perspective, showing the level of uncertainty between studies, overlaid with dots representing all the places specifically mentioned in the eight chapters of the main Assessment Report on Land Degradation and Restoration, including case studies of both degradation and restoration. Around the map are brief notes regarding the main forms of degradation encountered.</p>
Science Communication Webinar Series: Engaging with Policymakers
<p>Blue-Action coordinated a series of webinars on climate science communication in 2020. These are aimed at early-career researchers, but anyone who wishes to engage people with their research at any stage will find them valuable.</p> <p>This webinar was delivered on 15th October 2020 by Jan-Stefan Fritz, Managing Director of the German Marine Research Consortium. Stefan has over fifteen years experience linking science with European policymakers in Brussels, and here shares his wealth of experience in how and why we should be engaging with policy. </p>
TRANSFORM final conference: RRI and citizen engagement to open up regional R&I policymaking
<p>Three regions, three different approaches testing citizen and stakeholder engagement in regional R&I policy making... TRANSFORM partners from three regions - Catalonia, Brussels-Capital and Lombardy on their experiences, activities and impact beyond the project. The video was filmed during the TRANSFORM Final Conference which took place on 1 and 2 December in a hybrid format in Miland and online via Zoom. An opportunity to share project results and outcomes, learn and exchange with the RRI community.</p> <p>This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 872687. This video reflects only the authors' view. The European Research Executive Agency (REA) and the European Commission are not responsible for any use that may be made of the information it contains.</p>
Schematic and adapted figures from IPBES Sustainable Use of Wild Species Assessment - Summary for policymakers
<p>Schematic and adapted figures from the Summary for policymakers of the thematic assessment of the sustainable use of wild species of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES).</p>
Effects of an Evidence Service on Health System Policymakers' Use of Research Evidence
ClinicalTrials.gov study NCT01307228. IPD Sharing: NO. Countries: 1. Publications: 1.
Data for: Characterizing multi-criteria decision analysis, risk stratification, and hotspot analysis methods to optimise disease policymaking and evidence translation for medicines in low- and middle-income countries: A scoping review
Open the record for dataset details and reuse information.
IPBES Invasive Alien Species Assessment: Summary for Policymakers. Figures, tables and captions in Spanish
<p>Spanish translations of the figures, tables and their captions from the Summary for Policymakers of the Thematic Assessment Report on Invasive Alien Species and their Control of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services.</p>
Summary for Policymakers of the Assessment Report on Biodiversity and Ecosystem Services for Africa: Chapter 5 Systematic Review Database
<p>Systematic review database: results of the classification and analysis of scientific papers and reports, published between 2005 and 2016, that deal with scenarios of biodiversity and/or ecosystem services in Africa.</p>
Summary for Policymakers of the Assessment Report on Biodiversity and Ecosystem Services for Africa: Appendix 1.1 Methodology for Figure SPM.2
<p>Appendix 1.1 Methodology for Figure SPM.2</p>
Figure 9 in Summary for policymakers of the global assessment report on biodiversity and ecosystem services - unedited advance version
Figure 9. Transformative change in global sustainability pathways. Collaborative implementation of priority governance interventions (levers) targeting key points of intervention (leverage points) could enable transformative change from current trends towards more sustainable ones. Most levers can be applied by a range of actors such as intergovernmental organizations, governments, non-governmental organizations, citizen and community groups, indigenous peoples and local communities, donor agencies, science and educational organizations, and the private sector, at multiple leverage points, depending on context. Implementing existing and new instruments through place-based governance interventions that are integrative, informed, inclusive and adaptive, using strategic policy mixes and learning from feedback, could enable global transformation.
Figure 7 in Summary for policymakers of the global assessment report on biodiversity and ecosystem services - unedited advance version
Figure 7. Summary of recent status of, and trends in, aspects of nature and nature's contributions to people that support progress towards achieving selected targets of the Sustainable Development Goals. Selected targets are those where current evidence and target wording enable assessment of the consequences for target achievement of trends in nature and nature's contribution to people. Chapter 3 Section 3.3 provides a goal-level assessment of the evidence of links between nature and all Sustainable Development Goals. Scores for targets are based on systematic assessments of the literature and quantitative analysis of indicators where possible. None of the targets scored 'Full support' (that is, good status or substantial positive trends at a global scale); consequently, it was not included in the table. 'Partial support': the overall global status and trends are good or positive but insubstantial or insufficient, or there may be substantial positive trends for some relevant aspects but negative trends for others, or the trends are positive in some geographic regions but negative in others; 'Poor/Declining support': poor status or substantial negative trends at a global scale; "Uncertain relationship": the relationship between nature and/or nature's contributions to people and achieving the target; "Unknown": insufficient information to score the status and trends.
Figure 5. Development pathways since 1970 in Summary for policymakers of the global assessment report on biodiversity and ecosystem services - unedited advance version
Figure 5. Development pathways since 1970 for selected key indicators of human-environment interactions, which show a large increase in the scale of global economic growth and its impacts on nature, with strong contrasts across developed, developing, and least developed countries. Countries are classified according to the UN World Economic Situation and Prospects (www.un.org). Global gross domestic product has risen 4-fold in real terms with the vast majority of growth occurring in developed and developing countries (A). Extraction of living biomass (e.g. crops, fisheries) to meet the demand for domestic consumption and for export is highest in developing countries and rising rapidly (B). Material consumption per capita within each country (from imports and domestic production), however, is highest in developed countries (C). Overall protection of Key Biodiversity
Figure 4 in Summary for policymakers of the global assessment report on biodiversity and ecosystem services - unedited advance version
Figure 4. Contributions of indigenous peoples and local communities to the enhancement and maintenance of wild and domesticated biodiversity and landscapes. Indigenous and local knowledge systems are locally based, but regionally manifested and thus globally relevant. A wide diversity of practices actively and positively contribute to wild and domestic biodiversity through "accompanying" natural processes with anthropogenic assets (knowledge, practices and technology). Indigenous peoples often manage the land and coastal areas based on culturally specific world views, applying principles and indicators such as the health of the land, caring for the country and reciprocal responsibility. As lifestyles, values and external pressures change with globalization, however, unsustainable practices are becoming increasingly common in certain regions 9. The central figure shows the global-scale overlaps of 1) land areas traditionally owned, managed10, used, or occupied by indigenous peoples, 2) formally designated protected areas and 3) remaining terrestrial areas with very low human intervention (areas with <4 Human Footprint Index 11). Circles and intersections are proportional in area. Land areas traditionally owned, managed10, used, or occupied by indigenous peoples overlap with approx. 35 per cent of the area that is formally protected, and approximately 35 per cent of all remaining terrestrial areas with very low human intervention. Topics and pictures in the figure aim to illustrate, not represent, the types and diversity of the following contributions of indigenous peoples and local communities to biodiversity: (a) domestication and maintenance of locally adapted crop and fruit varieties (potatoes, Peru) and (b) animal breeds (rider and sheep, Kyrgyzstan) {2.2.4.4}; (c) creation of species-rich habitats and high ecosystem diversity in cultural landscapes (hay meadows, Central Europe) {2.2.4.1-2}; (d) identification of useful plants and their cultivation in high-diversity ecosystems (multi-species forest garden, Indonesia) {2.2.4.3}; (e)-(f) management and monitoring of wild species, habitats and landscapes for wildlife and for increased resilience (e) - Australia, (f) - Alaska) {2.2.4.5-6}; (g) restoration of degraded lands (Niger) {3.2.4}; (h) buffers for deforestation in recognized indigenous territories (Amazon basin, Brazil) {2.2.4.7}; (i) offering alternative concepts of relations between humanity and nature (Northern Australia).
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