Thesis (M.A.)--Carleton University, 2001. / Includes bibliographical references (p. 166-194). Also available in electronic format on the Internet.

Neglected Tropical Diseases (NTDs) are both causes and manifestations of poverty in developing countries. Recent advocacy efforts have increased the profile of NTDs, and led to bold new control and elimination targets set for 2020 by the World Health Organisation. However there are multifaceted challenges in effectively implementing NTD interventions in resource-poor contexts that need to be understood and engaged. While there is a growing call by researchers and international agencies for a science of global health delivery to understand these complexities, the exact nature of this science remains contested. This thesis contributes to these debates by advancing a critical social science perspective on the factors that mediate intervention effectiveness for NTD control. Grounded in a social constructivist approach using mixed methods, it critiques prevailing orthodoxies by unpacking the nature, processes and outcomes of three large-scale NTD prevention programmes in Eastern Africa. Focused on different diseases, these case studies represent different types of intervention approaches: top-down, participatory and public-private partnership. The thesis traces the social, technical and environmental processes that mediate the delivery, adoption and use of particular health technologies, such as pit latrines, insecticides and vaccination. Together, these case studies reveal surprisingly similar reasons for why many interventions do not perform according to expectations. Despite new approaches that claim to overcome stereotypical challenges of top-down planning, narrow technocratic perspectives continue to play a defining role in maintaining disjunctions between global aspirations, local realities and intervention outcomes. New perspectives and changes in orientation are needed that emphasise flexibility, learning and adaptability to local contexts. Towards this end, the thesis outlines a conceptual framework based on a comparative analysis of the case studies that highlights five interrelated domains where effectiveness is determined: geographical/livelihood variation, local agency, incentives, the socio-materiality of technology and planning/governance. I argue that addressing the shortcomings of contemporary interventions requires that programme planners actively engage these domains by seeking to “order complexity.” Greater integration of social science perspectives into the management of NTD programmes would provide significant benefit. In these ways, the thesis contributes to wider debates about the nature of global health interventions and the influence of local contexts in mediating efforts to improve the health and wellbeing of the world’s poor and marginalised.

This study investigates the effects that enrollment in a year’s social studies teacher training program emphasizing global education has on preservice social studies teachers’ teaching behaviors. A qualitative research effort supported by quantitative approaches was employed. A researcher-made questionnaire, the Social Studies Internship Inventory (SSII), was utilized along with classroom observations by a participant-observer. Subjects taking the SSII included all student teachers completing their internships in secondary social studies education during the 1988-1989 academic year. For the observational portion of this study, six subjects were selected from among the aforementioned group. Their student teaching placements were in a mixture of urban, suburban, and inner-city schools at both the junior and senior high school levels. Findings include: much of global education relies on the ability of the teacher to recognize a "critical teaching moment"; a curriculum that emphasizes a global perspective may depend more on the teacher than other curriculums; daily newspaper reading increased significantly between the beginning of the academic year and the end of the internship; a reversal occurred in the popularity of the television and newspaper as the main source of information over the course of the academic year (television news was watched more at the beginning? newspapers consulted more by the end); at the beginning of the study, 20% of the future teachers belonged to a professional organization; by the end of the program, 96% had memberships; though both the discrete and infusion approaches to global perspectives in education have their respective merits, a blending of the two was most effective; the role of the cooperating teacher seems to be crucial in imparting global perspectives to the student teacher; the university supervisor, who was trained in global perspectives, had an effect on the interns’ teaching; an unexpected finding was the great amount of student-talk observed; teachers who were most successful in teaching from a global perspective emphasized critical thinking skills and civic responsibility.

Block scheduling may mean that the schedule structure of a school is adapted to create longerlessons or that students have fewer subjects parallel to each other. This study examines how socialscience teachers in high school perceive that their didactic conditions change during blockscheduling. The study uses qualitative method in the form of interviews with four social scienceteachers at three different schools to find out how they adapt to block scheduling. The studyexamines the teachers’ thoughts regarding didactics with regards to block scheduling. Thedidactics refers to different educational purposes of social science, student assessment and otherconsiderations that the interviewed teachers consider to be important. The study highlights in what ways some schools and social science teachers have chosento work with block scheduling to strengthen their pupils’ prerequisites for learning. The studyshows that social science teachers at high schools may have positive experiences of blockscheduling. According to the interviewed teachers, extended lesson sessions may bring benefitssuch as flexibility in working methods and arrangements, an in-depth lesson content and a strongerinteraction between students and teacher. According to the interview teachers, block schedulingmay also lead to an increased workload for teachers, but this workload decreases over time.

The aim of this study is to examine how social science textbooks for upper secondary schools portrays the term “democracy”. Additionally, the study aims to examine the similarities and differences between the textbooks and determine the prevailing overall perspective on democracy. To help do this an analytical tool consisting of five criteria has been constructed based on Robert A. Dahl's theory on democratic processes and John Dewey's view on the role and importance of education for a democracy. These five criteria are: Effective participation/enlightened understanding, voting equality, control of the agenda, inclusiveness, and the role of education in a democracy. A total of six textbooks, based on the latest curriculum from 2011, have been examined and analysed.  The result and analysis of the study generally shows that the textbooks mainly focus on describing the formal democratic decision-making processes and principles without presenting any deeper reasoning for why these are important for democracy. In this context, representative democracy and direct democracy are often highlighted and compared to each other. The informal areas of society where democratic decision-making are made are generally only mentioned in passing or receive minor presentations. The role and importance of education for democracy are only mentioned in some of the textbooks, though school is often used as an example of an area of society where direct democracy is prevalent.  These are the overall similarities that exists across all textbooks. Some differences exist between the various textbooks, but these are only minor in nature. The main difference lies in what aspects of democracy each textbook chooses to highlight rather than the portrayal of democracy itself being any radically different.

Due to online social media, access to information is becoming easier and easier. Meanwhile, the truthfulness of online information is often not guaranteed. Incorrect information, often called misinformation, can have several modalities, and it can spread to multiple social media platforms in different languages, which can be destructive to society. However, academia and industry do not have automated ways to assess the impact of misinformation on social media, preventing the adoption of productive strategies to curb the prevalence of misinformation. In this dissertation, I present my research to build computational pipelines that help measuring and detecting misinformation on social media. My work can be divided into three parts. The first part focuses on processing misinformation in text form. I first show how to group political news articles from both trustworthy and untrustworthy news outlets into stories. Then I present a measurement analysis on the spread of stories to characterize how mainstream and fringe Web communities influence each other. The second part is related to analyzing image-based misinformation. It can be further divided into two parts: fauxtography and generic image misinformation. Fauxtography is a special type of image misinformation, where images are manipulated or used out-of-context. In this research, I present how to identify fauxtography on social media by using a fact-checking website (Snopes.com), and I also develop a computational pipeline to facilitate the measurement of these images at scale. I next focus on generic misinformation images related to COVID-19. During the pandemic, text misinformation has been studied in many aspects. However, very little research has covered image misinformation during the COVID-19 pandemic. In this research, I develop a technique to cluster visually similar images together, facilitating manual annotation, to make subsequent analysis possible. The last part is about the detection of misinformation in text form following a multi-language perspective. This research aims to detect textual COVID-19 related misinformation and what stances Twitter users have towards such misinformation in both English and Chinese. To achieve this goal, I experiment on several natural language processing (NLP) models to investigate their performance on misinformation detection and stance detection in both monolingual and multi-lingual manners. The results show that two models: COVID-Tweet-BERT v2 and BERTweet are generally effective in detecting misinformation and stance in the two above manners. These two models are promising to be applied to misinformation moderation on social media platforms, which heavily depends on identifying misinformation and stance of the author towards this piece of misinformation. Overall, the results of this dissertation shed light on understanding of online misinformation, and my proposed computational tools are applicable to moderation of social media, potentially benefitting for a more wholesome online ecosystem.

In the age of technology and with rapid expansion of social media outside of simply the social realm (entertainment), as it delves into the political realm, it is important to assess the implications that new technologies will have on our democracy. The purpose of this study is to attempt to predict the ramifications of the internet on American politics and the impact it is having on political norms and responsibilities. The norms that are expressly being examined are voter turnout and partisanship. We have seen in recent elections how individual candidates have utilized the internet to further their own campaigns and policy objectives. Indeed, President Barack Obama’s first campaign was hailed for its effective grassroots employment of social media to interact with young voters. This greatly contributed to his victory in the 2008 election over Republican John McCain. Donald Trump employed similar tactics in 2016, notoriously using Twitter to spread his message to his loyal base. President Trump also utilized claims of misinformation from the established political “gate-keepers” (i.e., mainstream media) to further push his narrative, further diminishing the power of established media outlets and propelling more people to alternative online outlets to receive their political information. This study looks at the long-term effects of such use, and how the voters are responding, and will seek to answer three main questions: (1) Are individuals outside of the typical voting elite (highly educated and/or wealthy) utilizing the internet for political purposes? (2) Does campaigning and/or policy projection via the web have any impact on election outcomes, or is it serving as another platform to reach out to an already loyal base? (3) Is the internet breaking down political divides and expanding the politically independent group, or has partisanship increased because of the internet?

No description available.

Social media platforms have become immensely popular over the years, leading to significant changes in cyberspace and the emergence of numerous challenges. These challenges have various faces, such as disinformation, online hate, cyberbullying, discrimination, biases, and other facets of harm. From the perspective of an end-user, the modern-age online ecosystem can be harmful in various ways, e.g., by consistently coming across disinformation in the online spaces or being targeted by a hate attack because of a specific ethnic or racial background. As we move forward, it is crucial to understand the nature and impact of new-age harms to make the Internet a safer place for everyone. To this end, my first contribution is the study of inauthentic accounts, also known as troll accounts. Troll accounts on social media are often sponsored by state actors aiming to manipulate public opinion on sensitive political topics. The strategy they commonly use is to interact with one another and appear innocuous to a regular user while covertly being used to spread toxic content and/or disinformation. I first study the effect that troll accounts have on online discussions on Reddit and show that state-sponsored troll accounts on Reddit produce threads that attract more toxic comments than other posts on the same subreddit. Next, I build TROLLMAGNIFIER, a detection system for troll accounts based on the observation that these accounts often exhibit loose coordination and interact with each other to advance specific narratives. TROLLMAGNIFIER learns the typical behavior of known troll accounts and identifies more that behave similarly. I show that using TROLLMAGNIFIER, one can grow the initial knowledge of potential trolls provided by Reddit by over 300%. Building upon the understanding of troll accounts and online campaigns, I then study the broader aspects of online disinformation. In this work, I study 19 influence campaigns on Twitter originating from various countries and identify several strategies adopted across different state actors, e.g., using scheduling services to delegate their posting tasks, utilizing fake third-party versions of popular applications (e.g., “Twitter for Android”) to post messages, extensively retweeting to push certain agendas, and posting innocuous messages (e.g., motivational quotes) to potentially avoid detection. Overall, I identify several universal traits among campaigns to create a cross-campaign detection system that can detect upto 94% accounts from unseen campaigns. Lastly, I delve deeper into the importance of cybersafety and study coordinated attacks, such as cyber-aggression and hate attacks, which are becoming increasingly common on video sharing networks like YouTube. Polarized online communities choose targets on prominent online platforms (e.g., YouTube) and organize their attacks by sending hateful messages to their target. The proposed system, TUBERAIDER, addresses this issue by automating the detection and attribution of attacks to their source communities, aiding in moderation, and understanding the motivations behind such actions. The system collects YouTube video links from diverse sources, including 4chan’s /pol/ board, r/The_Donald subreddit, and 16 incel subreddits. The attribution is performed through a machine learning classifier based on TF-IDF scores of important keywords and achieves an accuracy above 75% in attributing a coordinated attack to a given video. In summary, my research focuses on understanding, detecting, and combating online harms using a data-driven approach. I develop tools to mitigate the malicious behavior with the goal of offering policymakers guidelines to ensure user safety on social media platforms.

Communicative acts constitute organizations as social entities. I build upon the most structured previous analysis of this process, the four flows framework, by introducing a complex systems model of how organization emerges along a continuum, thereby enabling measurement of the growth and decline of partial organizations. I validate my approach using simulated data from two stochastic agent-based models and 30 historical case studies of insurgency. I show that the four flows may be used to assess the historical victor of a conflict, or to track the emergence of an organization from real-time communication network data. My results demonstrate the complex interrelationship of the four flows, and how they relate to social phenomena such as information asymmetry, individual versus group interest, governance, and the development of community structure. I reaffirm the centrality of these flows to the phenomenon of organization, while challenging the minimum requirements for it to begin, by showing that organization spontaneously emerges in a population as a result of markers of affiliation and human cognitive biases. / Doctor of Philosophy / Humans organize collective behavior by communicating. Prior research has shown that all organizations establish the costs and benefits of membership, distinctions from other organizations, enduring protocols, and approaches to short-term coordination. The strength with which organizations define each of these traits emerges on a continuum from a nascent organization to a robust one. My work is the first to place these acts of communication in an engineering model, showing how an organization works as a system to reduce collective uncertainty. I first explore my model in a computer simulation, demonstrating that each of the four processes can be measured. I then quantify the strength of each process in 30 case studies of insurgency, measuring the changing effectiveness of the insurgents and their state opponents at establishing themselves as the governing entity in an area. My technique accurately predicts the outcome of all 30 case studies. Finally, using a second simulation, I demonstrate measures of all four processes in communication records and show that organization may be the result of merely recognizing oneself as part of a group, amid basic patterns in human thinking, rather than evidence of cooperation toward shared objectives.