An evaluation of the grade level of business-sponsored teaching material

Thesis (M.A.)--Boston Universit

Finding Eyewitness Tweets During Crises

Disaster response agencies have started to incorporate social media as a source of fast-breaking information to understand the needs of people affected by the many crises that occur around the world. These agencies look for tweets from within the region affected by the crisis to get the latest updates of the status of the affected region. However only 1% of all tweets are geotagged with explicit location information. First responders lose valuable information because they cannot assess the origin of many of the tweets they collect. In this work we seek to identify non-geotagged tweets that originate from within the crisis region. Towards this, we address three questions: (1) is there a difference between the language of tweets originating within a crisis region and tweets originating outside the region, (2) what are the linguistic patterns that can be used to differentiate within-region and outside-region tweets, and (3) for non-geotagged tweets, can we automatically identify those originating within the crisis region in real-time

Formal Definitions of Conservative PDFs

Under ideal conditions, the probability density function (PDF) of a random variable, such as a sensor measurement, would be well known and amenable to computation and communication tasks. However, this is often not the case, so the user looks for some other PDF that approximates the true but intractable PDF. Conservativeness is a commonly sought property of this approximating PDF, especially in distributed or unstructured data systems where the data being fused may contain un-known correlations. Roughly, a conservative approximation is one that overestimates the uncertainty of a system. While prior work has introduced some definitions of conservativeness, these definitions either apply only to normal distributions or violate some of the intuitive appeal of (Gaussian) conservative definitions. This work provides a general and intuitive definition of conservativeness that is applicable to any probability distribution, including multi-modal and uniform distributions. Unfortunately, we show that this \emph{strong} definition of conservative cannot be used to evaluate data fusion techniques. Therefore, we also describe a weaker definition of conservative and show it is preserved through common data fusion methods such as the linear and log-linear opinion pool, and homogeneous functionals. In addition, we show that after fusion, weak conservativeness is preserved by Bayesian updates. These strong and weak definitions of conservativeness can help design and evaluate potential correlation-agnostic data fusion techniques

The effect of topic selection on writing fluency among Japanese high school students

Written fluency and fluency building activities have been shown to promote linguistic choice and student voice development, increased ability to express ideas using complex grammatical structures and greater intrinsic motivation in English language learners. Since the 1970’s, process-oriented writing has been emphasized, yielding an amplified focus on meaning of student content over linguistic form precision. Current research of writing fluency must delve deeper into questions of student ownership of topic and the outcomes for low-risk activities that support fluency practice and encourage confidence building in students. The purpose of this replication study is to further explore previous findings on the effects of topic selection on writing fluency for high school English as foreign language learners. Building off of the work of Bonzo (2008), this study focused on a timed, non-graded writing activity administered to groups of Japanese engineering students in three departments: mechanical, electrical, and global engineering. The six subsequent samples for each participating student were analyzed using online text-analysis for total and unique word counts, providing data used to perform a t-test. Responses to bi-lingual student questionnaires, with prompts on self-perceived written English ability, self-efficacy and strategies for success while writing, provided additional insight into the facets of fluency. The results of these writing sessions offer both confirmation of and contrast to Bonzo’s original work, demonstrate increased student meaning making, and support the use of free writing activities in English language classrooms as a means by which student written fluency may be improved

Disordered speech disrupts conversational entrainment: a study of acoustic-prosodic entrainment and communicative success in populations with communication challenges

Conversational entrainment, a pervasive communication phenomenon in which dialogue partners adapt their behaviors to align more closely with one another, is considered essential for successful spoken interaction. While well-established in other disciplines, this phenomenon has received limited attention in the field of speech pathology and the study of communication breakdowns in clinical populations. The current study examined acoustic-prosodic entrainment, as well as a measure of communicative success, in three distinctly different dialogue groups: (i) healthy native vs. healthy native speakers (Control), (ii) healthy native vs. foreign-accented speakers (Accented), and (iii) healthy native vs. dysarthric speakers (Disordered). Dialogue group comparisons revealed significant differences in how the groups entrain on particular acoustic–prosodic features, including pitch, intensity, and jitter. Most notably, the Disordered dialogues were characterized by significantly less acoustic-prosodic entrainment than the Control dialogues. Further, a positive relationship between entrainment indices and communicative success was identified. These results suggest that the study of conversational entrainment in speech pathology will have essential implications for both scientific theory and clinical application in this domain

Bayesian Hyperbolic Multidimensional Scaling

Multidimensional scaling (MDS) is a widely used approach to representing high-dimensional, dependent data. MDS works by assigning each observation a location on a low-dimensional geometric manifold, with distance on the manifold representing similarity. We propose a Bayesian approach to multidimensional scaling when the low-dimensional manifold is hyperbolic. Using hyperbolic space facilitates representing tree-like structures common in many settings (e.g. text or genetic data with hierarchical structure). A Bayesian approach provides regularization that minimizes the impact of measurement error in the observed data and assesses uncertainty. We also propose a case-control likelihood approximation that allows for efficient sampling from the posterior distribution in larger data settings, reducing computational complexity from approximately $O(n^2)$ to $O(n)$. We evaluate the proposed method against state-of-the-art alternatives using simulations, canonical reference datasets, Indian village network data, and human gene expression data

Family Policies and Public Health Initiatives: A Comparative Analysis of Breastfeeding Outcomes

Breastfeeding rates vary considerably among high-income countries who are members of the Organization for Economic Co-operation and Development (OECD). In the 1960's, breastfeeding outcomes, both initiation of breastfeeding and breastfeeding duration, were at an all-time low. Over the past half century, breastfeeding outcomes have increased among all OECD countries, but at very different rates. This dissertation examines both the policy-level and public health-level initiatives that have affected the differential growth of breastfeeding rates among 18 high-income, OECD countries. Using a combination of multiple regression, fuzzy-set qualitative comparative analysis, and small-n methods, I find that countries in the broad Scandinavian welfare regime have combined policy support for women's reproductive and productive labor, along with a strong female representation in government to facilitate positive breastfeeding outcomes. I find that countries who have a strong commitment to the World Health Organization's Baby-Friendly Hospital Initiative have higher breastfeeding initiation rates than countries who do not have a high percentage of hospitals following the WHO protocol. This dissertation adds to the broader understanding of how welfare state policies and public health initiatives operate in tandem to support positive breastfeeding outcomes among high-income countries

The effect of family policies and public health initiatives on breastfeeding initiation among 18 high-income countries: a qualitative comparative analysis research design

Abstract Background The objective of this study is to examine the effects of macro-level factors – welfare state policies and public health initiatives – on breastfeeding initiation among eighteen high-income countries. Methods This study utilizes fuzzy-set Qualitative Comparative Analysis methods to examine the combinations of conditions leading to both high and low national breastfeeding initiation rates among eighteen high-income countries. Results The most common pathway leading to high breastfeeding initiation is the combination of conditions including a high percentage of women in parliament, a low national cesarean section rate, and either low family spending, high rates of maternity leave, or high rates of women working part-time. The most common pathway leading to low breastfeeding initiation includes the necessary condition of low national adherence to the Baby-Friendly Hospital Initiative. Conclusion This research suggests that there is a connection between broad level welfare state polices, public health initiatives, and breastfeeding initiation. Compliance with the WHO/UNICEF initiatives depends on welfare regime policies and overall support for women in both productive and reproductive labor