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Machine Learning and Text Analysis Using Clustering, Classification, Categorization for Applied Industry Research and Its Effect on Trends and Prediction Analysis of a Doctor of Professionals Studies in Computing Dissertation Categories
No full textThe results of an industry research survey showed, understanding Dissertation Research categories has not been the focused on many researchers and institutions. This research expands on machine learning methodologies using two similar datasets to answer these three questions: 1. Is there a way to track the trends of Pace University’s Doctor of Professional Studies (DPS) student’s dissertation categories of the past 20 years using classification and categorizations? 2. Is it possible to determine dissertation trends in a professional doctorate program based on computing technology research? 3. Can we predict trends in DPS dissertation categories by analyzing the computing industry research? These questions were answered using Machine Learning and Text Analysis which created a four-step research methodology also known as the framework. These steps included: Clustering, Classification, Categorization, and Predictive Analysis on 113 DPS dissertations abstracts and comparing that against 98,393 IEEE research abstracts to predict future DPS categorization, specifically looking at the words in the predicted category. The findings of these three questions are as follows 1. A trend in DPS data was found using 240 clustered DPS words put into the classification model by year over the last 20 years showing each year\u27s categorization results. The trend shows the Algorithms category used most in the first five years, then Agile Practicing for the next five years. Finally, Cloud Technology becomes more dominant in later years. 2. There are dissertation trends in a professional doctorate program based on computing technology research. To get this trend, a second Classification model was used on the same DPS words in the new model. The trend depicted in the first five years; Algorithm category was the strongest. Then for the next five years, Cloud Computing became dominant. In the next five years, the trend changes to Software Development then, lastly Cloud Computing started trending. 3. The last part of the research questions predicted a DPS dissertation category trend by analyzing the computing industry research using IBM Watson’s predictive analysis tool. It predicted Cloud Computing as the category for DPS categories for the next five years, with the top 4 words used in this category being Data, Compute, Develop, and Cloud. Pace’s DPS program can now use this four-step process to help extend out their programs to help students\u27 find research categories using categorization and the text categories\u27 words
Scientific Gerrymandering & Bifurcation
Get PDFEnvironmental litigation must often examine the propriety of corporate conduct in areas of scientific complexity. In the second generation of climate nuisance suits, for example, allegations of corporate participation in the climate disinformation campaign are woven into plaintiffs’ claims. Toxic tort suits, currently and most notably in the Roundup and PFAS litigation, present another area of environmental litigation grappling with the legal ramifications of alleged corporate deception about scientific information. Toxic tort suits often surface allegations, and in many cases disturbing evidence, of what we term corporate “scientific gerrymandering”— corporate efforts to finesse, slow, or even mislead scientific understanding of the toxicity of chemicals and other products. The manner and extent to which scientific gerrymandering is explored and litigated within those suits is often driven by another typical feature of toxic tort litigation—the procedural device of bifurcation. Judges frequently bifurcate toxic tort suits into causation and negligence phases, with the causation phase heard first. Bifurcation in toxic tort suits involving issues of scientific gerrymandering requires judges to decide whether evidence of scientific gerrymandering is relevant to and may be presented during the causation phase of a toxic tort trial. And, typically, as Judge Vince Chhabria recently ruled in In re Roundup Products Liability Litigation (MDL No. 2741), judges hold that evidence of scientific gerrymandering cannot be presented or must be evidence of scientific gerrymandering cannot be presented or must be significantly limited during the causation phase because scientific gerrymandering is not relevant to causation.
Rulings that prevent admitting evidence of scientific gerrymandering during the causation phase of bifurcated trials can, however, be critiqued on both doctrinal and normative grounds. First, from a doctrinal perspective, scientific gerrymandering—how a corporate defendant shaped scientific knowledge about a product’s risk—is often directly relevant to causation— whether the product causes the relevant harm. This is so because effective corporate scientific gerrymandering can define the current state of science about product risk, particularly when questions about the extent of risk caused by a product lie at the frontiers of scientific knowledge. Additionally, numerous tort doctrines support shifting or reducing causal burdens in the face of defendant misconduct, like scientific gerrymandering—which might be likened to obscuring evidence.
Second, from a normative perspective, permitting consideration of scientific gerrymandering during causation can be justified even where the introduction of such evidence creates the risk that juries will erroneously find that a product causes harm. Condemnation of scientific gerrymandering is consistent with corrective justice because corporate scientific gerrymandering can occasion distinct and independent harm by creating a large group of exposed individuals who endure an extended period of fearful uncertainty until such time as the nature of that risk can be objectively resolved, even if that product is ultimately shown not to cause the suspected harm. Finally, from a policy perspective, allowing the introduction of evidence of corporate scientific gerrymandering during the causation phase of bifurcated toxic tort trials should discourage corporate actors from engaging in scientific gerrymandering, thereby improving the efficacy of regulation and bolstering public confidence
Environmental Law Disrupted By COVID-19
Get PDFFor over a year, the COVID-19 pandemic and concerns about systemic racial injustice have highlighted the conflicts and opportunities currently faced by environmental law. Scientists uniformly predict that environmental degradation, notably climate change, will cause a rise in diseases, disproportionate suffering among communities already facing discrimination, and significant economic losses. In this Article, members of the Environmental Law Collaborative examine the legal system’s responses to these crises, with the goal of framing opportunities to reimagine environmental law. The Article is excerpted from their book Environmental Law, Disrupted, to be published by ELI Press later this year
Dan Farkas
Get PDFDan Farkas has taught on the Pleasantville campus of Pace University since 1977.https://digitalcommons.pace.edu/oralhistory/1003/thumbnail.jp
Effective Cognitive Learning Solutions for Special Education Students of NYC Public Schools in Underserved Communities Prepared for: Dr. Sheying Chen Pace University
Get PDFThe goal of this report was to study scientific-based programs that promote the Theory of Cognition as the foundation to learning and teaching special education students and students classified as learning disabled in the public schools of under-served communities; to inform families who live and send their children to public schools in under-served communities of these alternative approaches to learning, inform them of their rights during IEP reviews and requesting an impartial hearing; and stop the School to Prison Pipeline. The research shows how students classified as special education in the most restrictive environment and students classified as Learning Disabled in the least restrictive environment benefit from such cognitive programs as well as why the specific diagnosis of a learning disability is paramount for finding the best learning program to meet a student’s needs. Additionally, the data shows how susceptible special education students and those receiving services under special education, from under-served communities are to becoming statistics within the School to Prison Pipeline; However, rather than investing funds in the proper education of all students through scientific-based programs, parents are forced to vie for funds and placements in schools and private programs to meet their children’s needs in a ‘Squeaky Wheel Gets the Oil’ fashion, proving to be counter to the idea of social equity throughout New York City Public Schools & to the overall idea of a Free And Appropriate Public Education (FAPE)
Who’s Watching: The Accuracy of Forecasting Broadcast TV Audience Demand Using Advertising Prices
Get PDFBroadcast and cable networks are struggling to keep up with the multitude of entertainment options available today, including but not limited to streaming services. However, these networks still play a role in the entertainment landscape. In order to maintain their role, they must first assess which shows deliver higher ratings and why. Ratings indicate audience demand for a particular show, which can be unpredictable. Regardless, networks sell commercial spots to advertisers at predetermined prices based on their expectations of future ratings, or demand. As such, this research paper focuses on broadcast networks and investigates two questions: Are broadcast networks able to accurately predict ratings, or audience demand, for their upcoming season of primetime shows, indicated by the predetermined prices for ad spots in the shows? If advertising prices do not reflect audience demand for the upcoming season, what is the reason for this? To address the research questions, a two-part mixed method design of both quantitative and qualitative research was used, showing that broadcast networks have been successful in predicting ratings for their upcoming primetime shows, but they should consider additional factors when creating shows to capture the most audience attention
The Impact of Subreddit Comments on Daily Return and Volume
Get PDFThis paper examines the subreddit WallStreetBets and its online weekday posts discussing stock market trades. By collecting data from the subreddit and Yahoo Finance, linear regression models are done using Rstudio to determine the relationship and impact that the number of comments has on percentage change in return and volume. This study concludes that when it comes to the relationship between returns and the number of comments, it is insignificant. However, we find that trading volume is positively and significantly related to the number of comments
Overhaul of the SDT Provisions in the WTO: Separating the Eligible from the Ineligible
Get PDFThe special and differential treatment (“SDT”) provisions have been a recurring feature in the agreements of the World Trade Organization (“WTO”) treaties. However, most analysts would probably agree that the many SDT provisions have been more aspirational than operational. Hence, there is little surprise that even a selective review of the WTO jurisprudence would demonstrate that the SDT provisions have, in most cases, not done enough for their intended beneficiaries. This paper will analyze the limitations of the SDT provisions with reference to the relevant WTO jurisprudence. It will seek to explore two potential avenues of endeavoring to make the SDT provisions engender more tangible outcomes for their intended beneficiaries. This article argues that although the two means discussed here may not seem connected, they indeed are
On Pills and Needles: Students’ and Clinical Nursing Faculty’s Lived Experience of a Nursing Student’s First Med Pass in the Clinical Setting
No full textLearning and teaching medication administration is a substantial component of prelicensure nursing education. The emphasis of the Quality and Safety Education for Nurses initiative is to prepare nursing students to provide safe, quality care. Medication administration, which falls under this initiative, is a challenge for nursing students to learn and for clinical nursing faculty to teach. Consequently, nursing students graduate feeling unprepared to administer medications in their practice. This issue is prevalent and long-standing within nursing education. Most of the research studies conducted, though, are from senior nursing students and nurses. There is little research from the beginner nursing student when first learning this skill and the faculty supervising them. Without an understanding of nursing students’ first experiences in medication administration and how faculty promote this clinical competency, strategies designed to prepare them for subsequent clinical and support them may be incongruent with their needs.This study used a phenomenological design to illuminate the lived experience of beginner nursing students’ first medication administration in the clinical setting from the student and faculty perspectives. Six nurses were interviewed about their student experience, and six faculty were interviewed about their experience with teaching and supervising beginner nursing students. Both groups’ experiences of this phenomenon contrasted and converged, as evidenced through their compelling stories. Using van Manen’s phenomenological method and Merleau-Ponty’s intersubjectivity, five essential themes emerged: (a) A Transformative Experience, (b) Unprepared for Complexities in the Clinical Environment, (c) Overcoming Fear Through Self-Reassurance and Faculty Support, (d) The Rubber Meets the Road: Administering Medications in the Actual Clinical Setting, and (e) Reaping the Rewards. The findings from this study will contribute to nursing education’s body of knowledge and benefit nursing professors and clinical nursing faculty who prepare beginner nursing students and supervise them administering medications in the clinical setting
