The Realities and Challenges of the Evacuation Topography Time Map

Dental trauma may occur in school settings and it can impact patients' quality of life. Analysis of the occurrences of dental trauma is essential in identifying preventive methods. There are numerous reports of such accidents but most are quantitative analyses with limited data. The aim of this study was to extract information on the mechanisms of injuries that leads to prevention by performing a qualitative analysis of the occurrence of dental trauma. After screening 7684 cases of dental injuries that occured in schools and were reported to the Japan Sports Council between 2005 and 2020, 533 detailed descriptions of injuries that occurred during sports were included. Quantitative text analysis was performed on the target data by performing statistical analysis, extracting frequently used words, and creating a co-occurrence network. Injury mechanisms were evaluated based on appearance of words. Dental injuries occurred frequently in five sports included in the survey. They were in order of decreasing frequency: baseball, basketball, soccer, volleyball, and rugby. Males were injured more often in all sports other than volleyball. The number of accidents increased in all sports among high school students. The frequent word list and co-occurrence network were different for each sport. This allowed typical accident occurrence mechanisms to be extracted for these five sports. Typical accident occurrence mechanisms were extracted from quantitative text analysis targeting free texts on the occurrence of accidents for five sports. Quantitative text analysis is useful for the evaluation of accident cases, which may aid in accident prevention.

The authors introduce readers to quantitative text analysis and its potential for analyzing text-based nonreactive measures as a means of broadening the evidential basis within research on giftedness and talent. After defining quantitative text analysis and describing how it can augment survey studies for analyses at individual and cultural levels, the special potential of quantitative text analysis for addressing cultural questions within gifted and talented research is described. Inductive and deductive techniques of quantitative text analysis are then introduced and illustrated with brief examples drawn from gifted and talented research. Finally, a brief illustrative study is presented via an extended series of linked worked examples focusing on the question of the place of giftedness and talent within mentoring discourse in US mass media of past and present in order to illustrate in more detail how quantitative text analysis can be used to improve the culture-level evidence base within gifted and talented education.

Quantitative text analysis refers to the application of one or more methods for drawing statistical inferences from text populations. After briefly distinguishing quantitative text analysis from linguistics, computational linguistics, and qualitative text analysis, issues raised during the 1955 Allerton House Conference are used as a vehicle for characterizing classical text analysis as an instrumental-thematic method. Quantitative text analysis methods are then depicted according to a 2 3 conceptual framework in which texts are interpreted either instrumentally (according to the researcher's conceptual framework) or representationally (according to the texts' sources' perspectives), as well as in which variables are thematic (counts of word/phrase occurrences), se- mantic (themes within a semantic grammar), or network-related (theme- or relation-positions within a conceptual network). Common methodological errors associated with each method are discussed. The paper concludes with a delineation of the universe of substantive answers that quantitative text analysis is able to provide to social science researchers.

Institutional policy processes (whether pre-legislative, legislative, post-legislative or administrative) in the European Union (EU) are probably among the most commonly misrepresented and misunderstood processes in Europe. The relationship between institutional actors and the general public, (mis-) informed and influenced by media outlets, is often hindered by high levels of distrust and by barriers to communication. One issue that has attracted considerable concern has been the role of vested interests, represented by large teams of lobbyists, in the development of legislation and regulations. This has led some to characterise the EU as having been captured by “big business”, to the detriment of Europe’s citizens. Yet while there is extensive circumstantial evidence of the ability of these interests to exert influence, for example through meetings with key decision-makers, and in a few cases from the inclusion of specific features in legislation (or a failure to legislate), it is more difficult to quantify such influence. One approach that has been considered to offer potential in this regard is quantitative text analysis (QTA). This refers to the application of one or more methods for drawing statistical inferences from text samples. In contrast, qualitative text analysis methods are comparatively more inductive, non-statistical and exploratory. QTA has been used to show a progressive shift away from language used in public health submissions on EU tobacco legislation towards that used by the industry. This study begins with the premise that industry, and especially multinational corporations, and possibly other stakeholder groupings (e.g. trade organizations, industry front groups) use particular vocabulary, evidence, position-taking and semantic shifts to influence the policy process. Business case language and economic perspectives dominate over a narrative featuring public health or ethical concerns. The study then explores the scope to use QTA as a tool to “interrogate” the subject (the text submitted to a public consultation), to examine and assess the content of public consultation documents and to evaluate the policy position of stakeholders as well as their evolution. Finally, it asks whether a more sophisticated package of tools, including QTA of policy briefs, mission statements or policy papers, can complement traditional methods such as stakeholder analysis to provide a more robust assessment that can protect public institutions against misuse and misrepresentation of scientific evidence in public consultations. I do this by investigating the experience of public consultations in influencing the evidence base for institutional policy-making in the field of health, aiming to identify who stands to benefit from public consultations and whether they achieve an advantage. I propose that QTA could help to foster a dialogue between groups weakly or rarely represented in public health consultations and institutional knowledge systems, and focus attention on the role of public consultations in challenging power hierarchies between public health activists, industry professionals and regulatory affairs practitioners as risk managers. I undertake QTA in three separate health-related case studies in which some variant of public consultation took place. This study looks at: a) the experience of public consultation applied to a draft scientific opinion by the European Food Safety Authority (on the chemical compound acrylamide), b) the process of consultation on the findings of an externally commissioned study on pharmaceutical pricing policy in Europe and c) the draft text sequence of an important piece of EU legislation as it progressed through the co-decision procedure, the application of rights of patients in cross-border healthcare, i.e. Directive 2011/24/EU.

Measuring how much two documents differ is a basic task in the quantitative analysis of text. Because difference is a complex, interpretive concept, researchers often operationalize difference as distance, a mathematical function that represents documents through a metaphor of physical space. Yet the constraints of that metaphor mean that distance can only capture some of the ways that documents can relate to each other. We show how a more general concept, divergence, can help solve this problem, alerting us to new ways in which documents can relate to each other. In contrast to distance, divergence can capture enclosure relationships, where two documents differ because the patterns found in one are a partial subset of those in the other, and the emergence of shortcuts, where two documents can be brought closer through mediation by a third. We provide an example of this difference measure, Kullback–Leibler Divergence, and apply it to two worked examples: the presentation of scientific arguments in Charles Darwin’s Origin of Species (1859) and the rhetorical structure of philosophical texts by Aristotle, David Hume, and Immanuel Kant. These examples illuminate the complex relationship between time and what we refer to as an archive’s “enclosure architecture”, and show how divergence can be used in the quantitative analysis of historical, literary, and cultural texts to reveal cognitive structures invisible to spatial metaphors.

An Introduction to Quantitative Text Analysis for Linguistics: Reproducible Research Using R is a pragmatic textbook that equips students and researchers with the essential concepts and practical programming skills needed to conduct quantitative text analysis in a reproducible manner. Designed for undergraduate students and those new to the field, this book assumes no prior experience with statistics or programming, making it an accessible resource for anyone embarking on their journey into quantitative text analysis. Through a pedagogical approach which emphasizes intuitive understanding over technical details, readers will gain data literacy by learning to identify, interpret, and evaluate data analysis procedures and results. They will also develop research skills, enabling them to design, implement, and communicate quantitative text analysis projects effectively. The book places a strong emphasis on programming skills, guiding readers through interactive lessons, tutorials, and lab activities using the R programming language and real-world datasets. This practical textbook is enriched with features that facilitate learning, including thought and practical exercises, a companion website that includes programming demonstrations to develop and augment readers’ recognition of how programming strategies are implemented, and a GitHub repository that contains both a set of interactive R programming lessons and lab exercises, which guide readers through practical hands-on programming applications. This textbook is an essential companion to any linguist looking to learn how to incorporate quantitative data analysis into their work. The Open Access version of this book, available at https://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.

Techniques of quantitative text analysis have successfully been utilized to extract policy positions from party manifestos and parliamentary speeches. This paper discusses the application of quantitative text analysis to new types of texts using the example of self-reported biographical notes from the Members of the German Parliament (MP). Arguing that party- and mandate-specific recruitment patterns shape the vocabulary MPs’ utilize in their biographical notes, we scale these texts using the word-fish/Austin approach. For the first time, we get a measure of the positions of all MP in the German Bundestag. In the course of the empirical study we show that this texts balance between the reporting of political careers on the one hand and strategic political communication on the other. We conclude that quantitative text analysis puts rather high requirements on the structure of the text corpus. The more successful external and formative factors, such as the purpose, context and length of the documents, are kept constant, the more helpful is quantitative text analysis for the identification of a substantially meaningful dimension.

Three UN world conferences held on reducing disaster damage – the 1994 World Conference on Natural Disaster Reduction held in Yokohama during the International Decade for Natural Disaster Reduction, the 2005 World Conference on Disaster Reduction held in Hyogo Prefecture, and the 2015 World Conference on Disaster Risk Reduction held in Sendai – resulted in the Yokohama Strategy and Plan of Action for a Safer World, the Hyogo Framework for Action 2005-2015 (HFA), and the Sendai Framework for Disaster Risk Reduction 2015-2030.The sections that follow clarify Sendai Framework features compared to the Yokohama Strategy and the HFA based on a three-stage review of the literature:1) Overviews of the three documents, including framework structures, are arranged with basic conference information and a comparative study.2) A quantitative text analysis is conducted using the KH Coder, which is free quantitative text analysis software. Words occurring frequently in the documents are extracted and compared and a co-occurrence network is analyzed to determine relationships among these words.3) Features of the three documents, mainly focusing on the Sendai Framework, are specified and clarified based on the result of quantitative text analysis.

Bullying continues to be a social issue affecting millions of students of all ages worldwide. Research on bullying seems to be dominated by quantitative research approaches employed standardized categories and measures, ultimately limiting our knowledge about children’s own view on bullying. Our research follows another direction, aiming to explore the representation of bullying in a sample of Italian primary school children by using and comparing the functioning of two qualitative research instruments: interviews, and children’s drawings. In addition, aided by quantitative analyses, we aimed to investigate whether students’ involvement in different bullying roles (as bullies, victims, or defenders), as measured by self-assessment, correlated with different characteristics of the representation of bullying emerging from children’s drawings and interviews. We recruited a convenient sample of 640 primary school students (mean age = 9.44; SD = 0.67), 53.3% of whom were male. The results showed that all forms of bullying, i.e., physical, verbal, and social bullying, could be identified in interview and drawing data, although references to all types of bullying were more frequent in interview data. In terms of bullying criteria, the presence of a power imbalance between the bully and the victim was most frequently detected in both the interview data and the drawing data, while repetition was more easily detected in the interview data. The interview data showed that sadness was the most frequently reported victim emotions, followed by fear, anger, and lack of emotion. The drawing data showed a similar pattern, although victims were more frequently described as lacking emotions compared to the interview data. In both interview and drawing data, age and female gender were positively associated with references to verbal bullying, and negatively associated with references to physical bullying. Additionally, bully/victim children were more likely than uninvolved children to depict physical bullying in the drawings, while this association was not detected in interview data. In summary, our study shows that, compared with drawings, interviews tend to provide a more comprehensive view of children’s own representation of bullying, while drawing data tend to show stronger connections with children’s current personal experiences of bullying.

Quantitative text analysis constitutes a promising new method that allows for measuring the policy positions and the lobbying success of interest groups by analyzing their submissions to legislative consultations ( Klüver, 2009 ). The use of quantitative text analysis allowed me to present a novel and unique research design which was the largest in scope at the time and resulted in important new insights regarding the determinants of lobbying success ( Klüver, 2009 , 2011 , 2013 ). In their recent article, Bunea and Ibenskas (2015) however question the usefulness of quantitative text analysis for studying interest groups and discuss several issues which in their view constitute important disadvantages of the technique. In this article I carefully discuss each of their arguments and show that none of their objections actually prevents scholars from successfully using quantitative text analysis to study interest groups in the European Union and beyond.

Since the end of the Cold War, the EU aims to advance to a relevant and autonomous actor in international politics—especially concerning security and defense politics. Scholars interested in whether the EU member states actually converge in their security and defense preferences often analyze strategy papers qualitatively, focusing on selected countries at specific points in time. In this article, we propose a dictionary approach for analyzing the development of security and defense preferences within the EU over the last three decades using quantitative text analysis. We make use of 163 strategy papers, published by all EU member states and the EU itself since 1994. The findings show that EU member states react similarly to international events, but do not converge substantially in their preferences. Furthermore, there is no substantial convergence to the position of the EU itself. We finally discuss usefulness and validity of quantitative text analysis in comparative research more broadly.

Despite the increased use of the term populism in vernacular and scholarly language, the measurement of the concept has long been neglected. The label is often attached to a certain party without any justification. Minimal definitions are alternatives but lack rigor. Classical content analyses provide more systematic measurements of populism but are extremely resource hungry. This article proposes an alternative, quantitative text analysis to measure the degree of populism among Belgian parties, drawing on both internally and externally oriented party literature. The results confirm that usual suspects such as the Vlaams Belang or Lijst Dedecker are the most populist of all parties under study. Populism turns out not to be an “either–or” concept, however, since we also identify a moderately populist party. It is furthermore demonstrated how populism can be attached to other ideologies, such as the radical right and (neo)liberalism. A cross‐validation of the proposed method with independent voter survey data confirms its validity. This article concludes that a quantitative text analysis might be a promising method to measure populism over time and space without the huge costs of hand coding.

Objectives This pilot study aimed to: 1) quantify the usage of “accident” and related terms in media articles describing agricultural injuries and fatalities involving children; and 2) assess journalists’ reactions to a suggested terminology shift from “accident” to “incident” in recent U.S. news media reports about youth agricultural injuries. Methods United States (U.S.) news reports covering agricultural injury events were obtained from the AgInjuryNews.org dataset. Quantitative text analysis was performed to identify news articles that mentioned “accident” or related terms (e.g., “accidental,” “accidentally”) in their title or narrative. Chi-square tests, post-hoc procedures, and univariate logistic regression were used to determine whether and to what extent “accident” and related terms were used to describe youth agricultural injuries. To assess journalists’ reactions to using “incident” instead of “accident” when describing youth agricultural injuries, a one-question survey was emailed to authors of news reports. Qualifying articles in the AgInjuryNews.org database were from June 1, 2022, to February 28, 2023, describing an agricultural injury involving victims under the age of 18 and featuring “accident” or its variations. Responses were coded based on sentiment. Results A total of 3,675 U.S. media reports were included in the quantitative text analysis for aim 1. “Accident” or related terms were used in 66% of the articles about youth agricultural injuries, compared to only 53% for reports about adult agricultural injuries. Agricultural injury events involving youth were more likely to be described using “Accident” or derived terms in U.S. news media than incidents involving adults (odds ratio: 1.73). For the second aim, 31 articles met the inclusion criteria for the journalists’ survey. The survey response rate was 39% (n = 12). Of the 12 journalists who responded, 1 disagreed with the proposed terminology shift, 5 were neutral, and 6 were in agreement. Conclusion The findings from the quantitative text analysis and survey results support the need for additional research and provide evidence to support efforts to create lasting change in the way youth agricultural injury and fatality events are reported by U.S. news media.

Journal Article Investigating macroscopic transitions in Japanese foreign policy using quantitative text analysis Get access Takafumi Suzuki Takafumi Suzuki * Faculty of Sociology, Tokyo University, Tokyo, Japan *E-mail: t_suzuki@nii.ac.jp Search for other works by this author on: Oxford Academic Google Scholar International Relations of the Asia-Pacific, Volume 11, Issue 3, September 2011, Pages 461–490, https://doi.org/10.1093/irap/lcr001 Published: 07 April 2011 Article history Received: 25 May 2010 Accepted: 11 February 2011 Published: 07 April 2011

Parents having new children during the coronavirus disease 2019 (COVID-19) pandemic were exposed to heightened parenting difficulties. However, pandemic-specific parenting difficulties and unmet support needs among these parents, especially fathers and parents with multiple children, remain underexplored. We conducted a study to clarify parenting difficulties and support needs of such parents by using quantitative text analysis of free-form descriptions collected from 809 Japanese parents in 2022 (first-child group: 163 fathers and 222 mothers; second-child group: 192 fathers and 232 mothers). Quantitative text analysis using KH Coder included co-occurrence network and correspondence analyses to identify parenting difficulties and support needs, stratified by sex, household income, and the presence of parenting consultants. Regarding parenting difficulties, fathers more often emphasized children's behavioral challenges, whereas mothers reported emotional struggles. Pandemic-related restrictions directly amplified parenting difficulties, including limited childcare resources, reduced social interaction, and infection-related concerns. Support needs across groups centered on financial assistance and childcare but varied by income, sex, and consultant availability. Fathers without consultants emphasized information and advice, while mothers without consultants stressed temporary childcare needs or illness-related support. Parenting difficulties and support needs reflected cultural gender norms. Policy implications include sustaining financial aid, developing gender-tailored interventions, and establishing crisis-resilient support systems.