On the Effect of Anticipation on Reading Times

Over the past two decades, numerous studies have demonstrated how less predictable (i.e., higher surprisal) words take more time to read. In general, these studies have implicitly assumed the reading process is purely responsive: Readers observe a new word and allocate time to process it as required. We argue that prior results are also compatible with a reading process that is at least partially anticipatory: Readers could make predictions about a future word and allocate time to process it based on their expectation. In this work, we operationalize this anticipation as a word's contextual entropy. We assess the effect of anticipation on reading by comparing how well surprisal and contextual entropy predict reading times on four naturalistic reading datasets: two self-paced and two eye-tracking. Experimentally, across datasets and analyses, we find substantial evidence for effects of contextual entropy over surprisal on a word's reading time (RT): in fact, entropy is sometimes better than surprisal in predicting a word's RT. Spillover effects, however, are generally not captured by entropy, but only by surprisal. Further, we hypothesize four cognitive mechanisms through which contextual entropy could impact RTs -- three of which we are able to design experiments to analyze. Overall, our results support a view of reading that is not just responsive, but also anticipatory.Comment: This is a pre-MIT Press publication version of the paper. Code is available in https://github.com/rycolab/anticipation-on-reading-time

Wildlife value orientations among diverse audiences in the American Southwest: helping state wildlife agencies broaden their constituent base

2013 Spring.Includes bibliographical references.There is growing recognition among wildlife professionals in the United States that although their decisions largely focus on topics biological in nature, the social, political, and economic ramifications of these decisions are considerable as well. As a result, social science is increasingly being included in the wildlife management decision-making process. At the same time, the constituencies that entrust state wildlife management agencies are diversifying, in terms of both their cultural heritage and their wildlife-related interests. To improve the effectiveness of agency efforts aimed at maintaining support from long-established stakeholders while simultaneously embracing emerging publics, there is a need to better understand the characteristics of diverse audiences. Wildlife value orientation (WVOs) theory offers an advantageous framework for systematically understanding the wildlife-related beliefs and interests of various segments of society. This dissertation investigates WVOs and their application across three diverse spectra: culture, methodology, and generations, each addressed in its own manuscript and through research conducted as part of a series of case studies occurring in Arizona. In Chapter II, WVOs are compared across cultures; specifically, this chapter explores possible differences and similarities in WVOs between Latinos and Caucasians. In addition to measuring WVOs, this study collected information about life values, wildlife-related attitudes, subjective norms, and behavioral intentions. Results indicated that Latinos perceive wildlife differently than Caucasians; however there was significant heterogeneity within Latino communities in the way they interacted with and related to wildlife. These findings provide managerial insight into engaging Latino communities in wildlife conservation issues as well as offer theoretical contributions by expanding the application of the WVO concept cross-culturally. In Chapter III, we introduce and test a mixed methods approach for measuring WVOs within Latino communities. As agencies are increasingly charged with managing wildlife for a broader clientele, including people of diverse demographic and cultural backgrounds, it raises questions about the potential limitations of traditional survey methodologies for cross-cultural WVO assessment. In the interest of addressing this concern we examined WVOs in Latino communities in Arizona using two quantitative and two qualitative methodologies. We found evidence that traditional quantitative WVO surveys may still be reliable for diverse audiences; however, we also identify scenarios wherein other methodologies may be advantageous. In Chapter IV, WVOs are compared across generations. As various cohorts of people across time experience different societal conditions believed to play a role in WVO formation, they can be grouped according to similar formative experiences. These generations experience various levels of urbanization, affluence, education, and technology, all contributing to distinctive life values. Concurrent with modernization is a value shift that is altering the way people perceive and interact with wildlife, specifically increasing the egalitarian perception that wildlife may serve as potential companions capable of trusting relationships with humans and who deserve caring and rights similar to those of humans. We confirmed there is a differential in the way generations perceive wildlife, suggesting agencies may want to consider engaging each cohort differently, according to how they relate to wildlife. These findings may assist agencies as they continue to engage broader constituencies and attempt to remain salient to younger generations. Overall, we found WVO theory to be a functional and robust framework for examining people's perceptions of wildlife across cultures, methodologies, and generations. Because of its durability, WVO theory shows promise for unifying research on human-wildlife relationships in a way that transcends space, time, and contextual situations. Additionally, WVOs have the practical utility of helping agencies understand the social context of wildlife conservation, and may assist agencies in comprehending changing societal conditions so they may be better prepared for the future of wildlife conservation

Adaptive Policy with Wait-kk Model for Simultaneous Translation

Simultaneous machine translation (SiMT) requires a robust read/write policy in conjunction with a high-quality translation model. Traditional methods rely on either a fixed wait-$k$ policy coupled with a standalone wait-$k$ translation model, or an adaptive policy jointly trained with the translation model. In this study, we propose a more flexible approach by decoupling the adaptive policy model from the translation model. Our motivation stems from the observation that a standalone multi-path wait-$k$ model performs competitively with adaptive policies utilized in state-of-the-art SiMT approaches. Specifically, we introduce DaP, a divergence-based adaptive policy, that makes read/write decisions for any translation model based on the potential divergence in translation distributions resulting from future information. DaP extends a frozen wait-$k$ model with lightweight parameters, and is both memory and computation efficient. Experimental results across various benchmarks demonstrate that our approach offers an improved trade-off between translation accuracy and latency, outperforming strong baselines.Comment: Accept to EMNLP 2023 main conference. 17 pages, 12 figures, 5 table

Leveraging Social Discourse to Measure Check-worthiness of Claims for Fact-checking

The expansion of online social media platforms has led to a surge in online content consumption. However, this has also paved the way for disseminating false claims and misinformation. As a result, there is an escalating demand for a substantial workforce to sift through and validate such unverified claims. Currently, these claims are manually verified by fact-checkers. Still, the volume of online content often outweighs their potency, making it difficult for them to validate every single claim in a timely manner. Thus, it is critical to determine which assertions are worth fact-checking and prioritize claims that require immediate attention. Multiple factors contribute to determining whether a claim necessitates fact-checking, encompassing factors such as its factual correctness, potential impact on the public, the probability of inciting hatred, and more. Despite several efforts to address claim check-worthiness, a systematic approach to identify these factors remains an open challenge. To this end, we introduce a new task of fine-grained claim check-worthiness, which underpins all of these factors and provides probable human grounds for identifying a claim as check-worthy. We present CheckIt, a manually annotated large Twitter dataset for fine-grained claim check-worthiness. We benchmark our dataset against a unified approach, CheckMate, that jointly determines whether a claim is check-worthy and the factors that led to that conclusion. We compare our suggested system with several baseline systems. Finally, we report a thorough analysis of results and human assessment, validating the efficacy of integrating check-worthiness factors in detecting claims worth fact-checking.Comment: 28 pages, 2 figures, 8 table

Sparse reduced-rank regression for imaging genetics studies: models and applications

We present a novel statistical technique; the sparse reduced rank regression (sRRR) model which is a strategy for multivariate modelling of high-dimensional imaging responses and genetic predictors. By adopting penalisation techniques, the model is able to enforce sparsity in the regression coefficients, identifying subsets of genetic markers that best explain the variability observed in subsets of the phenotypes. To properly exploit the rich structure present in each of the imaging and genetics domains, we additionally propose the use of several structured penalties within the sRRR model. Using simulation procedures that accurately reflect realistic imaging genetics data, we present detailed evaluations of the sRRR method in comparison with the more traditional univariate linear modelling approach. In all settings considered, we show that sRRR possesses better power to detect the deleterious genetic variants. Moreover, using a simple genetic model, we demonstrate the potential benefits, in terms of statistical power, of carrying out voxel-wise searches as opposed to extracting averages over regions of interest in the brain. Since this entails the use of phenotypic vectors of enormous dimensionality, we suggest the use of a sparse classification model as a de-noising step, prior to the imaging genetics study. Finally, we present the application of a data re-sampling technique within the sRRR model for model selection. Using this approach we are able to rank the genetic markers in order of importance of association to the phenotypes, and similarly rank the phenotypes in order of importance to the genetic markers. In the very end, we illustrate the application perspective of the proposed statistical models in three real imaging genetics datasets and highlight some potential associations

Volume VII

Volume VII of the Bulletin of Applied Linguistics published by the English Department of Morehead State University

SISME, estuarine monitoring system based on IOT and machine learning for the detection of salt wedge in aquifers: case study of the Magdalena river estuary

This article contains methods, results, and analysis agreed for the development of an application based on the internet of things and making use of machine learning techniques that serves as a support for the identification of the saline wedge in the Magdalena River estuary, Colombia. As a result of this investigation, the process of identifying the most suitable telecommunications architecture to be installed in the estuary is shown, as well as the characteristics of the software developed called SISME (Estuary Monitoring System), and the results obtained after the implementation of prediction techniques based on time series. This implementation supports the maritime security of the port of Barranquilla since it can support decision-making related to the estuary. This research is the result of the project “Implementation of a Wireless System of Temperature, Conductivity and Pressure Sensors to support the identification of the saline wedge and its impact on the maritime safety of the Magdalena River estuary”

Metaphors in the construction of theory: Ramus, Peirce and the American mind

This study argues for the mutual impenetration of logical, legal and scientific metaphors and attempts to determine the role played by them in the construction of theory. Specifically it attempts to discover the impact which the metaphors of topical logic may have had on the construction of American ideology. Chapter 1 offers a brief discussion of logical metaphors and their relation to the social and intellectual settings which generate them. Chapter 2 extends that discussion to principles of positive law and political order as they developed in the unstable atmosphere of 16th Century Europe. Chapters 3, 4 and 5 attempt to relate the metaphors defined in Chapters 1 and 2 to the development of the scientific models which emerged during the scientific revolution of the 17th Century. These chapters proceed in the context of a discussion of the interaction of Aristotelian, Cartesian and Ramean paradigms. Chapter 6 argues for the crucial importance of topical metaphors in the establishment of order in the American colonies. Chapters 7 and 8 carry the argument for a New England Mind into a national setting and discuss how Ramean metaphors contributed to the construction of American conceptions of political order and physical law. These chapters attempt to identify a controlling metaphor of continuity which operated at the base of American models. Chapter 9 claims this metaphor of continuity as the logical ground of pragmatic thought, transmitted to C. S. Peirce through the German logical tradition via Leibniz and Wolff. Chapter 10 extends that discussion to a specific investigation of Peirce\u27s Illustrations of the Logic of Science, considered here as representative of a fundamental commitment on Peirce\u27s part to a methodology which would underwrite the rest of his thought. Chapter 11 laments the failure of James, Dewey and Royce to appreciate the power of Peirce\u27s model and discusses the effect which their fragmentation of his continuous reality had on American philosophy. Peirce\u27s logic of science emerges as a fundamental expression of an American mind with roots sunk deep in a Ramean logical paradigm