The Educational Imaginary in Radical Reconstruction: Congressional Public Policy Rhetoric and American Federalism, 1862-1872

Facing the exigencies of Emancipation, a South in ruins, and ongoing violence, between 1862 and 1872 the United States Congress debated the role education would play in the postbellum polity. Positing schooling as a panacea for the nation’s problems, a determiner of individual worth, and a way of ameliorating state and federal tensions, congressional leaders envisioned education as a way of reshaping American political life. In pursuit of this vision, many policymakers advocated national school agencies and assertive interventions into state educational systems. Interrogating the meaning of “education” for congressional leaders, this study examines the role of this ambiguous concept in negotiating the contradictions of federal and state identity, projecting visions of social change, evaluating civic preparedness, and enabling broader debates over the nation’s future. Examining legislative debates over the Reconstruction Acts, Freedmen’s Bureau, Bureau of Education, and two bills for national education reform in the early 1870s, this project examines how disparate educational visions of Republicans and Democrats collided and mutated amid the vicissitudes of public policy argument. Engaging rhetorical concepts of temporality, disposition, and political judgment, it examines the allure and limitations of education policy rhetoric, and how this rhetoric shifted amid the difficult process of coming to policy agreements in a tumultuous era. In a broader historical sense, this project considers the role of Reconstruction Era congressional rhetoric in shaping the long-term development of contemporary Americans’ “educational imaginary,” the tacit, often unarticulated assumptions about schooling that inflect how contemporary Americans engage in political life, civic judgment, and social reform. Treating the analysis of public policy debate as a way to gain insights into transitions in American political life, the study considers how Reconstruction Era debate converged upon certain common agreements, and obfuscated significant fault lines, that persist in contemporary arguments.

Security and Trust in Distributed Computation

We propose three research problems to explore the relations between trust and security in the setting of distributed computation. In the first problem, we study trust-based adversary detection in distributed consensus computation. The adversaries we consider behave arbitrarily disobeying the consensus protocol. We propose a trust-based consensus algorithm with local and global trust evaluations. The algorithm can be abstracted using a two-layer structure with the top layer running a trust-based consensus algorithm and the bottom layer as a subroutine executing a global trust update scheme. We utilize a set of pre-trusted nodes, headers, to propagate local trust opinions throughout the network. This two-layer framework is flexible in that it can be easily extensible to contain more complicated decision rules, and global trust schemes. The first problem assumes that normal nodes are homogeneous, i.e. it is guaranteed that a normal node always behaves as it is programmed. In the second and third problems however, we assume that nodes are heterogeneous, i.e, given a task, the probability that a node generates a correct answer varies from node to node. The adversaries considered in these two problems are workers from the open crowd who are either investing little efforts in the tasks assigned to them or intentionally give wrong answers to questions. In the second part of the thesis, we consider a typical crowdsourcing task that aggregates input from multiple workers as a problem in information fusion. To cope with the issue of noisy and sometimes malicious input from workers, trust is used to model workers' expertise. In a multi-domain knowledge learning task, however, using scalar-valued trust to model a worker's performance is not sufficient to reflect the worker's trustworthiness in each of the domains. To address this issue, we propose a probabilistic model to jointly infer multi-dimensional trust of workers, multi-domain properties of questions, and true labels of questions. Our model is very flexible and extensible to incorporate metadata associated with questions. To show that, we further propose two extended models, one of which handles input tasks with real-valued features and the other handles tasks with text features by incorporating topic models. Our models can effectively recover trust vectors of workers, which can be very useful in task assignment adaptive to workers' trust in the future. These results can be applied for fusion of information from multiple data sources like sensors, human input, machine learning results, or a hybrid of them. In the second subproblem, we address crowdsourcing with adversaries under logical constraints. We observe that questions are often not independent in real life applications. Instead, there are logical relations between them. Similarly, workers that provide answers are not independent of each other either. Answers given by workers with similar attributes tend to be correlated. Therefore, we propose a novel unified graphical model consisting of two layers. The top layer encodes domain knowledge which allows users to express logical relations using first-order logic rules and the bottom layer encodes a traditional crowdsourcing graphical model. Our model can be seen as a generalized probabilistic soft logic framework that encodes both logical relations and probabilistic dependencies. To solve the collective inference problem efficiently, we have devised a scalable joint inference algorithm based on the alternating direction method of multipliers. The third part of the thesis considers the problem of optimal assignment under budget constraints when workers are unreliable and sometimes malicious. In a real crowdsourcing market, each answer obtained from a worker incurs cost. The cost is associated with both the level of trustworthiness of workers and the difficulty of tasks. Typically, access to expert-level (more trustworthy) workers is more expensive than to average crowd and completion of a challenging task is more costly than a click-away question. In this problem, we address the problem of optimal assignment of heterogeneous tasks to workers of varying trust levels with budget constraints. Specifically, we design a trust-aware task allocation algorithm that takes as inputs the estimated trust of workers and pre-set budget, and outputs the optimal assignment of tasks to workers. We derive the bound of total error probability that relates to budget, trustworthiness of crowds, and costs of obtaining labels from crowds naturally. Higher budget, more trustworthy crowds, and less costly jobs result in a lower theoretical bound. Our allocation scheme does not depend on the specific design of the trust evaluation component. Therefore, it can be combined with generic trust evaluation algorithms.

Strong shift equivalence, algebraic K-theory, and isolating zero-dimensional dynamics on manifolds

We study the relations of shift equivalence and strong shift equivalence for matrices over a ring $\mathcal{R}$, and establish a connection between these relations and algebraic K-theory. We utilize this connection to obtain results in two areas where the shift and strong shift equivalence relations play an important role: the study of finite group extensions of shifts of finite type, and the Generalized Spectral Conjectures of Boyle and Handelman for nonnegative matrices over subrings of the real numbers. We show the refinement of the shift equivalence class of a matrix $A$ over a ring $\mathcal{R}$ by strong shift equivalence classes over the ring is classified by a quotient $NK_{1}(\mathcal{R}) / E(A,\mathcal{R})$ of the algebraic K-group $NK_{1}(\calR)$. We use the K-theory of non-commutative localizations to show that in certain cases the subgroup $E(A,\mathcal{R})$ must vanish, including the case $A$ is invertible over $\mathcal{R}$. We use the K-theory connection to clarify the structure of algebraic invariants for finite group extensions of shifts of finite type. In particular, we give a strong negative answer to a question of Parry, who asked whether the dynamical zeta function determines up to finitely many topological conjugacy classes the extensions by $G$ of a fixed mixing shift of finite type. We apply the K-theory connection to prove the equivalence of a strong and weak form of the Generalized Spectral Conjecture of Boyle and Handelman for primitive matrices over subrings of $\mathbb{R}$. We construct explicit matrices whose class in the algebraic K-group $NK_{1}(\mathcal{R})$ is non-zero for certain rings $\mathcal{R}$ motivated by applications. We study the possible dynamics of the restriction of a homeomorphism of a compact manifold to an isolated zero-dimensional set. We prove that for $n \ge 3$ every compact zero-dimensional system can arise as an isolated invariant set for a homeomorphism of a compact $n$-manifold. In dimension two, we provide obstructions and examples.

On Experiencers and Minimality

This dissertation is concerned with experiencer arguments, and what they tell us about the grammar. There are two main types of experiencers I discuss: experiencers of psychological verbs and experiencers of raising constructions. I question the notion of ‘experiencers’ itself; and explore some possible accounts for the ‘psych-effects’. I argue that the ‘experiencer theta role’ is conceptually unnecessary and unsustained by syntactic evidence. ‘Experiencers’ can be reduced to different types of arguments. Taking Brazilian Portuguese as my main case study, I claim that languages may grammaticalize psychological predicates and their arguments in different ways. These verb classes exist in languages independently, and the psych-verbs behavior can be explained by the argument structure of the verbal class they belong to. I further discuss experiencers in raising structures, and the defective intervention effects triggered by different types of experiencers (e.g., DPs, PPs, clitics, traces) in a variety of languages. I show that defective intervention is mostly predictable across languages, and there’s not much variation regarding its effects. Moreover, I argue that defective intervention can be captured by a notion of minimality that requires interveners to be syntactic objects and not syntactic occurrences (a chain, and not a copy/trace). The main observation is that once a chain is no longer in the c-command domain of a probe, defective intervention is obviated, i.e., it doesn’t apply. I propose a revised version of the Minimal Link Condition (1995), in which only syntactic objects may intervene in syntactic relations, and not copies. This view of minimality can explain the core cases of defective intervention crosslinguistically.

When Love Becomes Hate(?): The Interplay Between Consumer-Brand Relationships and Crisis Situations

This study had three purposes. First, it aimed to re-conceptualize organization-public relationships (OPRs) in public relations and crisis communication. This OPR re-conceptualization helps find out when the OPR buffering effect or the OPR love-becomes-hate effect happens. Second, it aimed to examine how consumer emotions are influenced by OPRs and influence consumer behavioral intentions. Third, it aimed to address the current problematic operationalization of the concept of consumer. Three pilot studies and one main study were conducted. Apple and Whole Foods were the two brands examined. One crisis that undermined the self-defining attributes shared between the brand and its consumers and another crisis that did not were examined for each brand. Almost 500 Apple consumers and 400 Whole Foods consumers provided usable questionnaires. This study had several major findings. First, non-identifying relationship and identifying relationship were different constructs. Moreover, trust, satisfaction, and commitment were not conceptually separate dimensions of OPRs. Second, the non-identifying relationships offered buffering effects by increasing positive attitudes and tempering anger and disappointment. The identifying relationships primarily offered the love-becomes-hate effects by increasing anger and disappointment. Third, if the crisis was relevant to consumers’ daily lives, brand response strategies were less effective at mitigating consumer negative reactions. Moreover, apology-compensation-reminder strategy was more effective compared to no-comment strategy. However, the apology-compensation-reminder strategy was no more effective than other strategies as long as brands compensate to the victims. Identifying relationships increased the effectiveness of response strategies. If the crisis did not undermine the self-defining attributes shared between consumers and brands, the response strategies worked even better. This study contributes to crisis communication research in multiple ways. First, it advances the OPR conceptualization by demonstrating that non-identifying relationship and identifying relationship are different concepts. More importantly, it advances the theory building of OPRs’ influences on crises by finding out when the buffering effect and the love-becomes-hate effect happen. Second, it adds to emotion research by demonstrating that strong OPRs can lead to negative emotions and positive emotions can have negative behavioral consequences on organizations. Third, the precise operationalization of the concept of consumer gives more insights about consumer reactions to crises.