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119 results for “Justice”
Classification of majority opinions and headnotes written by U.S. Supreme Court Justice Antonin Scalia
<p>This is data to accompany an article by Linda L. Berger and Eric C. Nystrom, "A Rhetorical-Computational Analysis of Justice Antonin Scalia's 'Remarkable Influence': The Unexpected Importance of Deceptively Unanimous and Contested Majority Opinions," <em>Journal of Appellate Practice and Process</em> 20, no. 2 (2020).</p> <p>In "scalia-HN-with-ruletype.tsv," Berger classified each headnote from a Scalia-authored majority opinion as one of the following rhetorical types: argument, scalia rule, or preexisting rule. (See article for further explanation of these categories.) Organized by SCDB ID and headnote number.</p> <p>In "unanimity.tsv," Berger addressed each case with a Scalia-authored majority opinion, assessing the degree of unanimity, which may or may not be the same as that implied by the for/against vote in the case. Fields include case SCDB ID, majority-minority vote, and degree of unanimity.</p> <p>Both data files are in Tab-separated format. For further information, please contact the authors.</p>
Database of indicators to evaluate the contribution of urban nature-based solutions to climate change adaptation, biodiversity conservation, and social justice
<p>Supplementary data used within the publication: Goodwin, S., Olazabal, M., Castro, A. J., & Pascual, U. (2024). Measuring the contribution of nature-based solutions beyond climate adaptation in cities. <em>Global Environmental Change</em>, <em>89</em>, 102939. <a href="https://doi.org/10.1016/j.gloenvcha.2024.102939">https://doi.org/10.1016/j.gloenvcha.2024.102939</a>. Please also cite this paper when citing this database.</p> <div> <div>Within this database, you can find a list of indicators used to evaluate the contribution of a collection of 74 nature-based solutions (NbS) to climate change adaptation and related biodiversity and social justice challenges in cities. This list of indicators may be useful to those working in cities to provide inspiration for similar indicators they may wish to use to evaluate NbS in their city. This collection of NbS was drawn from previous work published in <em>Nature Sustainability</em> <a href="https://rdcu.be/c4tjk">here</a>.</div> <div> </div> </div> <p><em>The project that gave rise to these results received the support of a fellowship from the “la Caixa” Foundation (ID 100010434). The fellowship code is “LCF/BQ/DI20/11780006”. Marta Olazabal’s research is funded by the European Union (ERC, IMAGINE adaptation, 101039429). This research is further supported by María de Maeztu Excellence Unit 2023-2027 (ref. CEX2021-001201-M), funded by the Ministerio de Ciencia, Innovación y Universidades/Agencia Estatal de Investigación (AEI) (Spain) (MCIN/AEI/10.13039/501100011033/); and by the Basque Government through the BERC 2022-2025 program. </em></p> <p><em>Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.</em></p>
Dataset from: A quiet public? Procedural justice in Portuguese wind energy governance
<p>This dataset accompanies a journal article related with public participation in wind and solar energy in Portugal. It contains a database of web scraped public consultation processes related with wind power plants and decentralized solar power plants until 2023. It also contains the R Markdown files that were used to analyze the scraped data. The results of this analyzes, and their discussion, can be found in the associated article.</p>
Abstracts that contain "justice" from AGU Fall Meeting 2014-2024
<p>CSV containing a list of abstracts from AGU Fall Meetings 2014-2024 that contain the word "justice" in the title or text of the abstract. Abstracts were assembled by searching the individual Fall Meeting confex pages and copying the information directly into a CSV. </p> <p>The file contains the conference year, abstract number, full text of the abstract, and a characterization of the sector of the authors, based on listed affiliation in the AGU Fall Meeting system. The sectors include academic, governmental, NGO, commercial, informal education, and cross-sector.</p>
Corpus of Decisions: Permanent Court of International Justice (CD-PCIJ)
<p> </p> <p><strong>Overview</strong></p> <p>The <strong>Corpus of Decisions: Permanent Court of International Justice (CD-PCIJ)</strong> collects and presents for the first time in human- and machine-readable formats all documents of PCIJ Series A, B and A/B of the <a href="https://www.icj-cij.org/en/pcij">Permanent Court of International Justice (PCIJ)</a>. Among these are judgments, advisory opinions, orders, appended minority opinions, annexes, applications instituting proceedings and requests for an advisory opinion. The International Court of Justice, the successor of the PCIJ, has kindly made available these documents <a href="https://www.icj-cij.org/en/pcij">on its website</a>.</p> <p>The <a href="https://www.icj-cij.org/en/pcij">Permanent Court of International Justice (PCIJ)</a> was the primary judicial organ of the League of Nations, the ill-fated predecessor of the United Nations, which existed from 1920 to 1946. Nonetheless, as the first international court with general thematic jurisdiction, the PCIJ influenced international law in profound ways that are still felt today. Every lawyer who sets out on the path of international law encounters epoch-defining opinions such as the <em>Lotus</em> and <em>Factory at Chorzów</em> decisions, but the Court's lesser-known jurisprudence and the appended minority opinions offer many more ideas and legal principles which are seldom appreciated today.</p> <p>This data set is designed to be complementary to and fully compatible with the <strong><a href="https://doi.org/10.5281/zenodo.3826445">Corpus of Decisions: International Court of Justice (CD-ICJ)</a></strong>, which is also available open access.</p> <p> </p> <p><strong>Citation</strong></p> <p>A peer-reviewed academic paper describing the construction and relevance of the data set entitled <strong><a href="https://doi.org/10.1111/jels.12313">'Introducing Twin Corpora of Decisions for the International Court of Justice (ICJ) and the Permanent Court of International Justice (PCIJ)'</a></strong> was published open access in the <a href="https://doi.org/10.1111/jels.12313">Journal of Empirical Legal Studies (JELS)</a>. It is also available in print at JELS 2022, Vol. 19, No. 2, pp. 491-524.</p> <p>If you use the data set for academic work, please cite both the JELS paper and the precise version of the data set you used for your analysis.</p> <p> </p> <p><strong>NEW in Version 1.1.0</strong></p> <ul> <li>Full recompilation of data set</li> <li>CHANGELOG and README converted to external markdown files</li> <li>Display of version number on Codebook and Compilation Report title pages fixed; correctly display semantic versioning</li> <li>The ZIP archive of source files includes the TEX files</li> <li>Config file converted to TOML format</li> <li>All R packages are version-controlled with {renv}</li> <li>Data set creation process cleans up all files from previous runs before a new data set is created</li> <li>Remove redundant color from violin plots</li> </ul> <p> </p> <p><strong>Updates</strong></p> <p>The CD-PCIJ will only be updated if <a href="https://github.com/SeanFobbe/cd-pcij/issues">errors are discovered</a>, enhancements are developed or in the unlikely event that the Court publishes additional documents within the collection ambit of the data set (PCIJ Series A, B and A/B).</p> <p>Notifications regarding new and updated data sets will be published on my academic website at <a href="https://seanfobbe.com/">www.seanfobbe.com</a> or via Mastodon at <a href="https://fediscience.org/@seanfobbe">@seanfobbe@fediscience.org</a></p> <p> </p> <p><strong>Recommended Variants</strong></p> <table summary="Recommended variants"> <thead> <tr> <th scope="col">Target Audience</th> <th scope="col">Recommended Variant</th> </tr> </thead> <tbody> <tr> <td><em>Practitioners</em></td> <td>PDF_ENHANCED_MajorityOpinions</td> </tr> <tr> <td><em>Traditional Scholars</em></td> <td>PDF_ENHANCED_FULL</td> </tr> <tr> <td><em>Quantitative Analysts</em></td> <td>CSV_TESSERACT_FULL</td> </tr> </tbody> </table> <p> </p> <p>Please refer to the Codebook regarding the relative merits of each variant. All variants are available in either English or French. Unless you have very specific needs you should only use the variants denoted 'ENHANCED' or 'TESSERACT' for serious work.</p> <p> </p> <p><strong>Features</strong></p> <ul> <li>Fully compatible with the <a href="https://doi.org/10.5281/zenodo.3826445">Corpus of Decisions: International Court of Justice (CD-ICJ)</a></li> <li>29 variables</li> <li>Public Domain (CC-Zero 1.0)</li> <li>Open and platform independent file formats (PDF, TXT, CSV)</li> <li>Extensive Codebook</li> <li><a href="https://zenodo.org/record/7051937/files/CD-PCIJ_1-1-0_CompilationReport.pdf?download=1">Compilation Report</a> explains construction and validation of the data set in detail</li> <li>Large number of diagrams for all purposes (see the 'ANALYSIS' archive)</li> <li>Diagrams are available as PDF (for printing) and PNG (for web display), tables are available as CSV for easy readability by humans and machines</li> <li>Secure cryptographic signatures</li> <li><a href="https://doi.org/10.5281/zenodo.7051937">Publication of full source code (Open Source)</a></li> </ul> <p> </p> <p><strong>Key Metrics</strong></p> <p><em>Version:</em> 1.1.0</p> <p><em>Temporal Coverage</em>: 22 May 1922 – 26 February 1940</p> <p><em>Documents:</em> 259 (English) / 261 (French)</p> <p><em>Tokens:</em> 1,296,536 (English) / 1,262,184 (French)</p> <p><em>Formats:</em> PDF, TXT, CSV</p> <p> </p> <p><strong>Source Code and Compilation Report</strong></p> <p>With every compilation of the full data set an <a href="https://zenodo.org/record/7051937/files/CD-PCIJ_1-1-0_CompilationReport.pdf?download=1">extensive Compilation Report</a> is created in a professionally layouted PDF format (comparable to the Codebook). The Compilation Report includes the Source Code, comments and explanations of design decisions, relevant computational results, exact timestamps and a table of contents with clickable internal hyperlinks to each section. The Compilation Report and Source Code are published under the same DOI: <a href="https://doi.org/10.5281/zenodo.7051937">https://doi.org/10.5281/zenodo.7051937</a></p> <p>For details of the construction and validation of the data set please refer to the Compilation Report.</p> <p> </p> <p><strong>Disclaimer</strong></p> <p>This data set has been created by Mr Seán Fobbe using documents available on the website of the International Court of Justice (<a href="https://www.icj-cij.org">https://www.icj-cij.org</a>). It is a personal academic initiative and is not associated with or endorsed by the International Court of Justice or the United Nations.</p> <p>The Court accepts no responsibility or liability arising out of my use, or that of third parties, of the documents and information produced, used or published on the Zenodo website. Neither the Court nor its staff members nor its contractors may be held responsible or liable for the consequences, financial or otherwise, resulting from the use of these documents and information.</p> <p> </p> <p><strong>Academic Publications (Fobbe)</strong></p> <p>Website — <a href="https://www.seanfobbe.com">www.seanfobbe.com</a></p> <p>Open Data — <a href="https://zenodo.org/communities/sean-fobbe-data/">zenodo.org/communities/sean-fobbe-data</a></p> <p>Code Repository — <a href="https://zenodo.org/communities/sean-fobbe-code/">zenodo.org/communities/sean-fobbe-code</a></p> <p>Regular Publications — <a href="https://zenodo.org/communities/sean-fobbe-publications/">zenodo.org/communities/sean-fobbe-publications</a></p> <p> </p> <p><strong>Contact</strong></p> <p>Did you discover any errors? Do you have suggestions on how to improve the data set? You can either post these to the <a href="https://github.com/SeanFobbe/cd-pcij/issues">Issue Tracker on GitHub</a> or write me an e-mail at <a href="mailto:fobbe-data@posteo.de">fobbe-data@posteo.de</a></p> <p> </p>
Qualitative dataset - Social justice-oriented narratives in European urban food strategies: Bringing forward redistribution, recognition and representation (Smaal et al., 2021)
<p>This qualitative dataset contains the English translations of the plain texts of the urban food strategy documents or webpages of 16 European medium-sized cities: Basel [CH]; Bristol [UK]; Bruges [BE]; Cordoba [ES]; Donostia - San Sebastián [ES]; Ede [NL]; Geneva [CH]; Ghent [BE]; Grenoble [FR]; Groningen [NL]; Montpellier [FR]; Nantes [FR]; Rennes [FR]; Tours [FR]; Uppsala [SE]; and Vitoria-Gasteiz [ES]. The search for and translation of the urban food strategy documents and webpages have been performed in early 2019. The files have been analysed in NVivo (qualitative data analysis software). The upload also includes figures and a table with the authors' assessments connected to the resources and services codes and radar diagram visualisations presented in the following paper: </p> <p>Smaal, S. A. L., Dessein, J., Wind, B. J., & Rogge, E. (2021). Social justice-oriented narratives in European urban food strategies: Bringing forward redistribution, recognition and representation. <em>Agriculture and Human Values</em>, 38(3), 709–727. <a href="http://doi.org/10.1007/s10460-020-10179-6">https://doi.org/10.1007/s10460-020-10179-6</a> </p> <p><strong>Abstract: </strong>More and more cities develop urban food strategies (UFSs) to guide their efforts and practices towards more sustainable food systems. An emerging theme shaping these food policy endeavours, especially prominent in North and South America, concerns the enhancement of social justice within food systems. To operationalise this theme in a European urban food governance context we adopt Nancy Fraser’s three-dimensional theory of justice: economic redistribution, cultural recognition and political representation. In this paper, we discuss the findings of an exploratory document analysis of the social justice-oriented ambitions, motivations, current practices and policy trajectories articulated in sixteen European UFSs. We reflect on the food-related resource allocations, value patterns and decision rules these cities propose to alter and the target groups they propose to support, empower or include. Overall, we find that UFSs make little explicit reference to social justice and justice-oriented food concepts, such as food security, food justice, food democracy and food sovereignty. Nevertheless, the identified resources, services and target groups indicate that the three dimensions of Fraser are at the heart of many of the measures described. We argue that implicit, fragmentary and unspecified adoption of social justice in European UFSs is problematic, as it may hold back public consciousness, debate and collective action regarding food system inequalities and may be easily disregarded in policy budgeting, implementation and evaluation trajectories. As a path forward, we present our plans for the RE-ADJUSTool that would enable UFS stakeholders to reflect on how their UFS can incorporate social justice and who to involve in this pursuit.</p> <p><em>This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 765389. </em></p> <p>Project webpage: <a href="https://recoms.eu/">https://recoms.eu/</a></p>
Black Lives, British Justice: Black people in London Criminal Justice Records 1720-1841
<p>This dataset brings together all 698 known references to ‘Black’ or possibly Black African heritage people or groups in records of London criminal justice (1720-1841). Each entry includes references to primary sources mentioning the person(s), including in the <em>Old Bailey Proceedings</em>, <em>Ordinary’s Accounts</em>, and <em>Middlesex Criminal Registers</em>. Individuals are trial witnesses, victims, defendants, and people mentioned in passing during testimony. For each entry, a confidence level is offered by the authors, as a person’s ethnicity cannot always be determined with certainty. Evidence for making that judgment is provided. This dataset is useful for anyone interested in Black history in Britain, Black people and justice, or Black London during the age of enslavement.</p> <p>Significant background material is available on the Old Bailey Online website, which provides additional context for these records. The authors also recommend the following works:</p> <p> * Kathleen Chater. <em>Untold Histories: Black People in England and Wales during the Period of the British Slave Trade, c. 1660-1807</em> (Manchester, 2011).<br> * Norma Myers, <em>Reconstructing the Black Past</em> (Frank Cass, 1996).<br> * Marika Sherwood. ‘Blacks in the Gordon Riots’, <em>History Today</em>, vol. 47 (1997), 24-28.</p> <p><br> Each record includes details on the name of the Black individual(s), as well as information on up to three sources in which he/she/they have been identified, and an indication by the authors on the likelihood the person is actually Black.</p> <p>Each entry has 17 columns of data, all of which are described in full in the ReadMe.txt file.</p>
JUSTNORTH Justice Database
<p>JUSTNORTH is an EU-funded climate action project exploring the perspectives and values that stakeholders can bring to Arctic economic decision-making.</p> <p>The JUSTNORTH Justice Database is the final outcome of the project's work with theories and frameworks of justice. It is a database of bibliographic materials organised in folders related to schools of justice philosophy (i.e., libertarianism, feminism) and applied approaches (i.e., environmental, energy) in justice. It also includes folders for grey literature and justice organisations. The database is intended to be a study and research resource for its users, both within JUSTNORTH and for those researching issues of justice beyond the project. </p> <p>This dataset includes Access and Excel versions that can be downloaded, there is also a living version on Zotero (https://www.zotero.org/groups/4662062/justnorth_justice_database/library). JUSTNORTH received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 869327.</p>
An Innovative Scheme to Confront the Trade‐Off Between Water Conservation and Heat Alleviation With Environmental Justice for Urban Sustainability: The Case of Phoenix, Arizona
<p><em><strong>The manuscript for this dataset is accepted by AGU Advances and can be accessed here: <a href="https://doi.org/10.1029/2022AV000816">link</a>. Please cite the literature when using the datasets.</strong></em></p> <p><strong>How to cite this article: Yuanhui Zhu, Soe Myint, Xin Feng, Yubin Li. An Innovative Scheme to Confront the Trade‐Off Between Water Conservation and Heat Alleviation With Environmental Justice for Urban Sustainability: The Case of Phoenix, Arizona. AGU Advances, 4, e2022AV000816. <a href="https://doi.org/10.1029/2022AV000816">https://doi.org/10.1029/2022AV000816</a></strong></p> <p>This study aims to develop a practical and integrated framework to tackle the tradeoff between land surface temperature (LST) reduction and water conservation for heat mitigation and resilience planning in Phoenix, Arizona. We developed a multi-objective framework of spatial optimization for priority areas that considers environmental justice. We employed the priority areas (i.e., residential districts, socio-economically disadvantaged neighborhoods, hotspot regions, and opportunity areas), ECOSTRESS-based LST, actual evapotranspiration (ETa, as a proxy to water use), Landsat-based LST and ETa changes (2000–2020), and the evaporative stress index (ESI). These datasets are used to identify the priority areas in which environmental conditions need to be improved seriously and (2) spatially optimize the placement of new green space (tree %, grass %) in the priority areas to realize the most significant LST reduction and minimum OWU. We provide the results of the new green space configurations with the scenarios for the percentage of new vegetation coverage (including trees and grass) overall increased to 25%, 35%, and 45% within the entire study areas, residential districts, socio-economically disadvantaged neighborhoods, and hotspot regions.</p> <table> <caption>The dataset summarization</caption> <tbody> <tr> <td>Category</td> <td>Dataset</td> <td>Resolution</td> <td>Source/method</td> <td>Time</td> </tr> <tr> <td>Environmental database</td> <td>Summer daytime LST</td> <td>70m</td> <td>ECOSTRESS</td> <td>2019</td> </tr> <tr> <td>Environmental database</td> <td>Summer nighttime LST</td> <td>70m</td> <td>ECOSTRESS</td> <td>2019</td> </tr> <tr> <td>Environmental database</td> <td>Summer ETa</td> <td>70m</td> <td>ECOSTRESS</td> <td>2019</td> </tr> <tr> <td>Environmental database</td> <td>Summer ESI</td> <td>70m</td> <td>ECOSTRESS</td> <td>2019</td> </tr> <tr> <td>Environmental change database</td> <td>Trends of summer LST changes</td> <td>30m</td> <td>Landsat-based Statistical Mono-Window algorithm</td> <td>2000-2020</td> </tr> <tr> <td>Environmental change database</td> <td>Trends of summer ETa changes</td> <td>30m</td> <td>Landsat-based Simplified Surface Energy Balance</td> <td>2000-2020</td> </tr> <tr> <td>The results of new green space configurations</td> <td>The spatial distributions of new green space</td> <td>--</td> <td>Spatial optimization</td> <td>--</td> </tr> </tbody> </table> <p>note: LULC: Land use and land cover; LST: Land Surface Temperature; ETa: Actual Evapotranspiration; ESI: Evaporative Stress Index</p> <p>We provide the different scenarios in shapefile format for spatial distributions of new space configurations. The naming convention for attribute tables in shapefile is :</p> <p>VV_new_perNN_LSTWW</p> <p>where:</p> <ul> <li>VV = New vegetation for tree or grass</li> <li>NN = The scenarios with new vegetation increased to 25%, 35%, or 45% (unit: %)</li> <li>WW = The weight values of land surface temperature range from 0 to 1 (unit: %) when executing spatial optimization for the tradeoff between land surface temperature reduction and outdoor water use conservation with vegetation coverage. The weight of 0 represents that our spatial optimization models only focus on outdoor water use conservation, and the weight of 1 denotes that we only consider land surface temperature reduction. </li> </ul> <p>Example: grass_new_per25_LST65 means -- new vegetation for grass; the scenario is set up by new vegetation increased to 25%; the weight of land surface temperature is 0.65. </p> <p> </p>
Data for: A path forward: creating an academic culture of justice, equity, diversity and inclusion
<p>Institutions of higher education (IHE) throughout the United States have a long history of acting out various levels of commitment to diversity advancement, equity, and inclusion (DEI). Despite decades of DEI "<em>efforts</em>," the academy is fraught with legacies of racism that uphold white supremacy and prevent marginalized populations from full participation. Furthermore, politicians have not only weaponized education but passed legislation to actively ban DEI programs and censor general education curricula (<a href="https://tinyurl.com/antiDEI">https://tinyurl.com/antiDEI</a>). Ironically, systems of oppression are particularly apparent in the fields of Ecology, Evolution, and Conservation Biology (EECB)–which recognize biological diversity as essential for ecological integrity and resilience. Yet, amongst EECB faculty, people who do not identify as cis-heterosexual, non-disabled, affluent white males are poorly represented. Furthermore, IHE lack metrics to quantify DEI as a priority. Here we show that only 30.3% of US-faculty positions advertised in EECB from Jan 2019-May 2020 required a diversity statement; diversity statement requirements did not correspond with state-level diversity metrics. Though many announcements "encourage women and minorities to apply," empirical evidence demonstrates that hiring committees at most institutions did not prioritize an applicant's DEI advancement potential. We suggest a model for change and call on administrators and faculty to implement SMART (i.e., Specific, Measurable, Achievable, Realistic, and Timely) strategies for DEI advancement across IHE throughout the United States. We anticipate our quantification of diversity statement requirements relative to other application materials will motivate institutional change in both policy and practice when evaluating a candidate's potential "fit". IHE must embrace a leadership role to not only shift the academic culture to one that upholds DEI, but to educate and include people who represent the full diversity of our society. In the current context of political censure of education including book banning and backlash aimed at Critical Race Theory, which further reinforce systemic white supremacy, academic integrity and justice are more critical than ever. </p>
Organizational justice and health
<p>Data concerning the study on organizational justice, sjob strain and mental health in hospital workers</p>
U.S. cities increasingly integrate justice into climate planning and create policy tools for climate justice (Diezmartínez & Short Gianotti, 2022) - Data and code
<p>This repository contains datasets and coding corresponding to the journal article titled "U.S. cities increasingly integrate justice into climate planning and create policy tools for climate justice". We include:</p> <ul> <li>DataRegressionAnalysis.csv <ul> <li>CSV file with data used for regression analysis. This file can be used directly to run R code provided in this repository.</li> </ul> </li> <li>QualitativeCodingResults.nvp <ul> <li>NVivo project with all results for the qualitative coding of urban climate action plans.</li> <li>This file also contains all climate action plans analyzed in this research.</li> </ul> </li> <li>QualitativeCodingResults_Summary.xlsx <ul> <li>Excel file with a results summary for the qualitative coding of urban climate action plans.</li> </ul> </li> <li>RegressionAnalysis.Rmd <ul> <li>Rmd file with R code used for regression analysis. </li> </ul> </li> <li>RegressionAnalysis_KnitOutput.html <ul> <li>Knit output from R code with regression analysis results, html format.</li> </ul> </li> <li>RegressionAnalysis_KnitOutput.pdf <ul> <li>Knit output from R code with regression analysis results, PDF format.</li> </ul> </li> </ul>
Social justice implications of smart urban technologies: an intersectional approach
<p><strong><em>Abstract</em></strong></p> <p>Techno-optimistic visions around smart buildings, homes, cities, grids, healthcare etc. have become ubiquitous over the past decade. Utilizing variations of machine learning and artificial intelligence, smart urbanism (SU) envisions an efficient, digital society. However, research shows that smart technologies reinscribe inequalities by prioritizing the interests of the free market, technology-centric governance, and data monetization. Although there has been a growing concern over the injustices SU perpetuates, there is a lack of systematic engagement with power systems such as capitalism or heterosexism that underpin SU visions. In this paper, we develop a novel framework which situates intersectional justice at the heart of SU. A mapping of 70 cases of ‘trouble’ with the promises of SU is carried out to address three core research questions: (i) What are the ‘troubles’ with SU? (ii) To what extent are they intersectional? and (iii) What can intersectionality add to the development of a just SU? Our analysis shows how SU politics play out in relation to how users are understood and engaged, how different actors institutionalise SU, and how dominant power systems are challenged. We find that intersectional justice concerns are addressed only marginally - 1 of the 70 cases explicitly mentioned the term intersectionality, 16 did not engage with any intersectional approach, and 31 cases did not address social justice concerns directly.</p> <p><strong><em>Practice Relevance:</em></strong> (i) <em>citizen-led initiatives</em> against SU should commit to intersectionality’s radical core to dismantle power structures to ensure local smart urban projects do not entrench global business-as-usual neoliberal agendas. Intersectional thinking can create spaces for deliberative dialogues between civil society groups and build alliances across groups that seek to challenge the hegemony of exclusionary urban policies, (ii) <em>urban planners and local governments</em> which are at the forefront of SU applications should decenter technologies and rather focus efforts on working out how smart technologies can work <em>in conjunction </em>with other kinds of urban interventions, such as social, economic and environmental policy changes, collaborative planning, community development, etc to herald more just urban futures and (iii) <em>designers of smart urban technologies</em> should apply intersectional approaches to further challenge <em>homoeconomicus</em> (rational, white, technophilic, able-bodied) as the primary user-type and to replace it with diverse user archetypes that express humanity, justice, and generosity.</p>
Data for: A path forward: creating an academic culture of justice, equity, diversity and inclusion
Open the record for dataset details and reuse information.
Data From: Emissions redistribution and environmental justice implications of California's Clean Vehicle Rebate Project
Open the record for dataset details and reuse information.
Day 115: Justice corps
Mural on [Herkimer & Nostrand, Brooklyn](https://www.google.com/maps/@40.6796502,-73.9497767,3a,60.4y,347.72h,92.49t/data=!3m6!1e1!3m4!1s93aUmp_d0rGsXHH7L3Xa1g!2e0!7i16384!8i8192). Captured with iPhone 12 lidar + Polycam *I'm trying to post 1 scan a day in 2021. You can follow the tag [#1scanaday](http://sketchfab.com/tags/1scanaday), or my [2021 collection here](https://sketchfab.com/alban/collections/1-scan-a-day-in-2021). You can also join at anytime, as long as you try keeping up from there. My tips on iphone lidar scanning: http://bit.ly/lidarscanning* Source: Objaverse 1.0 / Sketchfab
Conservative News Media and Criminal Justice: Evidence from Exposure to Fox News Channel
<p>Conservative News Media and Criminal Justice: Evidence from Exposure to Fox News Channel" (Elliott Ash and Michael Poyker), <i>Economic Journal</i>, 2023</p>
Lion, palais de justice d'Orléans - France
This sculpture of a lion, located at the entrance of the Orléans' courthouse, was made by the french sculptor Louis-Alexandre Romagnesi in year 1824. Before being placed at the courthouse, these lions were located in the castle of Châteauneuf-sur-Loire, in the same province. Source: Objaverse 1.0 / Sketchfab
Palace of Justice lobby lion
 Today, the Palace of Justice is perceived only as the XIX building of the Lviv Polytechnic National University, but few know what role this pasty building has played in the past. The building began its legendary journey from antiquity to the present in 1891. Then, according to the plans of the Polish architect Francis Skovron, the palace was erected for the Supreme Court of Galicia. Once in the middle of the room, in the lobby we will see two stone lions, which symbolized the protection of the law and laws of Galicia. They were performed by the author of the monument to Adam Mickiewicz in Lviv, Anton Popel. Created in RealityCapture by Capturing Reality. Shot on Lumia 930. Source: Objaverse 1.0 / Sketchfab
Data for manuscript: "Themes in Academic Literature: Prejudice and Social Justice"
<p>This data set contains frequency counts of target words in 175 million academic abstracts published in all fields of knowledge. We quantify the prevalence of words denoting prejudice against ethnicity, gender, sexual orientation, gender identity, minority religious sentiment, age, body weight and disability in SSORC abstracts over the period 1970-2020. We then examine the relationship between the prevalence of such terms in the academic literature and their concomitant prevalence in news media content. We also analyze the temporal dynamics of an additional set of terms associated with social justice discourse in both the scholarly literature and in news media content. A few additional words not denoting prejudice are also available since they are used in the manuscript for illustration purposes.</p> <p>The list of academic abstracts analyzed in this work was taken from the Semantic Scholar Open Research Corpus (SSORC). The corpus contains, as of 2020, over 175 million academic abstracts, and associated metadata, published in all fields of knowledge. The raw data is provided by Semantic Scholar in accessible JSON format.</p> <p>Textual content included in our analysis is circumscribed to the scholarly articles’ titles and abstracts and does not include other article elements such as main body of text or references section. Thus, we use frequency counts derived from academic articles’ titles and abstracts as a proxy for word prevalence in those articles. This proxy was used because the SSORC corpus does not provide the entire text body of the indexed articles. Targeted textual content was located in JSON data and sorted by year to facilitate chronological analysis. Tokens were lowercased prior to estimating frequency counts.</p> <p>Yearly relative frequencies of a target word or n-gram in the SSORC corpus were estimated by dividing the number of occurrences of the target word/n-gram in all scholarly articles within a given year by the total number of all words in all articles of that year. This method of estimating word frequencies accounts for variable volume of total scientific output over time. This approach has been shown before to accurately capture the temporal dynamics of historical events and social trends in news media corpora.</p> <p>It is possible that a small percentage of scholarly articles in the SSORC corpus contain incorrect or missing data. For earlier years in the SSORC corpus, abstract information is sometimes missing and only article’s title information is available. As a result, the total and target word count metrics for a small subset of academic abstracts might not be precise. In a data analysis of 175 million scientific abstracts, manually checking the accuracy of frequency counts for every single academic abstract is unfeasible and hundred percent accuracy at capturing abstracts’ content might be elusive due to a small number of erroneous outlier cases in the raw data. Overall, however, we are confident that our frequency metrics are representative of word prevalence in academic content as illustrated by Figure 2 in the main manuscript, which shows the chronological prevalence in the SSORC corpus of several terms associated with different disciplines of scientific/academic knowledge.</p> <p>Factor analysis of frequency counts time series was carried out only after Bartlett’s test of sphericity and Kaiser-Meyer-Olkin (KMO) test confirmed the suitability of the data for factor analysis. A single factor derived from the frequency counts time series of prejudice-denoting terms was extracted from each corpus (academic abstracts and news media content). The same procedure was applied for the terms denoting social justice discourse. A factor loading cutoff of 0.5 was used to ascribe terms to a factor. Chronbach alphas to determine if the resulting factors appeared coherent were extremely high (>0.95).</p> <p>The textual content of news and opinion articles from the outlets listed in Figure 5 of the main manuscript is available in the outlet's online domains and/or public cache repositories such as Google cache (https://webcache.googleusercontent.com), The Internet Wayback Machine (https://archive.org/web/web.php), and Common Crawl (https://commoncrawl.org). We used derived word frequency counts from original sources. Textual content included in our analysis is circumscribed to articles headlines and main body of text of the articles and does not include other article elements such as figure captions.</p> <p>Targeted textual content was located in HTML raw data using outlet specific xpath expressions. Tokens were lowercased prior to estimating frequency counts. To prevent outlets with sparse text content for a year from distorting aggregate frequency counts, we only include outlet frequency counts from years for which there is at least 1 million words of article content from an outlet. </p> <p>Yearly frequency usage of a target word in an outlet in any given year was estimated by dividing the total number of occurrences of the target word in all articles of a given year by the number of all words in all articles of that year. This method of estimating frequency accounts for variable volume of total article output over time.</p> <p>The list of compressed files in this data set is listed next:</p> <p>-analysisScripts.rar contains the analysis scripts used in the main manuscript and raw data metrics</p> <p>-scholarlyArticlesContainingTargetWords.rar contains the IDs of each analyzed abstract in the SSORC corpus and the counts of target words and total words for each scholarly article</p> <p>-targetWordsInMediaArticlesCounts.rar contains counts of target words in news outlets articles as well as total counts of words in articles</p> <p>In a small percentage of news articles, outlet specific XPath expressions can fail to properly capture the content of the article due to the heterogeneity of HTML elements and CSS styling combinations with which articles text content is arranged in outlets online domains. As a result, the total and target word counts metrics for a small subset of articles might not be precise. </p> <p>In a data analysis of millions of news articles, we cannot manually check the correctness of frequency counts for every single article and hundred percent accuracy at capturing articles’ content is elusive due to the small number of difficult to detect boundary cases such as incorrect HTML markup syntax in online domains. Overall however, we are confident that our frequency metrics are representative of word prevalence in print news media content (see Rozado, Al-Gharbi, and Halberstadt, “Prevalence of Prejudice-Denoting Words in News Media Discourse" for supporting evidence).</p> <p>31/08/2022 Update: There is a new way to download the Semantic Scholar Open Research Corpus (see https://github.com/allenai/s2orc). This updated version states that the corpus contains 136M+ paper nodes. However, when I downloaded a previous version of the corpus in 2021 from http://s2-public-api-prod.us-west-2.elasticbeanstalk.com/corpus/download/ I counted 175M unique identifiers. The URL of the previous version of the corpus is no longer active, but it has been cached by the Internet Archive at https://web.archive.org/web/20201030131959/http://s2-public-api-prod.us-west-2.elasticbeanstalk.com/corpus/download/ I haven't had the time to look at the specific reason for the mismatch but perhaps the newer version of the corpus has cleaned a lot of noisy entries in the previous version which often contained entries with missing abstracts. Filtering out entries in low prevalence languages other than English might be another reason. In any case, Figure 2 of the main manuscript of this work (at https://www.nas.org/academic-questions/35/2/themes-in-academic-literature-prejudice-and-social-justice) should provide support for the validity of the frequency counts.</p> <p> </p>
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