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Derived Relational Responding, Transformation of Psychological Stimulus Functions, and Avoidance in Mothers of Clinically Referred Children for Anxiety and Related Disorders
Get PDFAccommodation is a parenting behavior that is highly prevalent, has a strong association with child anxiety, and that persists despite its deleterious effects (e.g., Benito et al., 2015; Lebowitz et al., 2013; Thompson-Hollands, Kerns, Pincus, & Comer, 2014). While little is known about the psychological processes that motivate parents to engage in accommodating behaviors, conceptual models suggest that parental behavior may be influenced by avoidance of parental distress and cognitions around child anxiety (e.g., Feinberg, Kerns, Pincus, & Comer, 2018; Jones, Lebowitz, Marin, & Stark, 2015). However, most of the research in this domain is correlational, precluding knowledge regarding the possible influence or function that parents’ perceptions of their children’s anxiety may have on their parenting behavior. Relational frame theory (RFT; Hayes, Barnes-Holmes, & Roche, 2001), a behavioral-analytic account of human language and cognition, allows for the experimental research of cognitive processes, as it conceptualizes cognitions as verbal behavior. The purpose of the present study was to explore derived relational responding in parents of anxious children and its potential role in avoidance based parenting behavior. Specifically, five parents of anxious children provided words describing their children’s anxiety (aversive stimuli), sources of joy (appetitive stimuli), descriptions of neutral objects (neutral stimuli) and positive parenting values (appetitive stimuli for a second experiment). This study used an alternating treatments single case experimental design across participants to explore latency and errors in derived relations across the three stimulus classes. I expected that mothers would: Hypothesis One: Form equivalence classes faster and with fewer errors between aversive child anxiety and novel stimuli relative to neutral novel or appetitive-novel stimuli, Hypothesis Two: take more time and make more errors in forming classes with aversive child anxiety stimuli and parenting values stimuli, compared to neutral-parenting values and appetitive-parenting values stimuli, Hypothesis Three: avoid visual stimuli previously associated with child anxiety stimuli, and Hypothesis Four: self-report elevated perception of child anxiety, parental avoidance, autonomy granting behavior and Hypothesis Five: self-report elevated cognitive fusion, experiential avoidance, and trait anxiety. Hypotheses were partially supported. Most mothers formed functional equivalence classes among novel symbols and aversive child anxiety words faster and with less errors than when forming relations between novel symbols and either neutral or appetitive words. Mothers did not show a systematic tendency to form equivalence classes with stimuli of incongruent psychological functions more slowly or with more errors than when forming classes between other stimuli. While participants 1 through 4 selected symbols systematically, only 1 and 3 avoided the symbols that had acquired aversive psychological functions on all trials. Results support the possibility that parents of anxious children may be less sensitive to other stimuli when stimuli about their children’s anxiety is present. Limitations of this study include not having a participant whose child did not struggle with anxiety, as well as some novel stimuli having psychological properties prior to the experimental tasks. Other implications are discussed
The Pandemic Syllabus
Get PDFA syllabus is a contract, an introduction, a statement of values, a todo list, a plan. It is often the point of first contact between professor and student, or between student and an area of law. Beyond the technological challenges, for many professors Fall 2020 was also the first-time coming up with a camera policy or amending attendance expectations to consider a pandemic. For some, this is also the first time explicitly engaging in antiracist pedagogy in the classroom or considering practices like trauma informed teaching. This essay offers a practical, “nuts and bolts” walkthrough of promising practices for each part of the syllabus while also touching on complex pedagogical questions such as issues of accessibility, setting a cooperative tone for class, and preparing students for sometimes challenging discussions. This essay is not only about the transition to online teaching, but more broadly about shifts within legal education that only promise to become more relevant. The essay is a practical and helpful guide for those planning future semesters, even in a post-pandemic world
The Horror of Stephen King’s Stereotyped Female Characters
Get PDFThrough four original works of fiction, each entitled The Knock, I have tested in a literary experiment the extent to which the stereotypes and archetypes present in three of Stephen King\u27s female characters box in the characters and how the characters may influence plot. I also test one original character, free of intentional types
Oral History Interview with Anthony Merzlak (SOH-055 video recording and transcript)
No full textTony Merzlak, Professor Emeritus of English and past department chair, discusses his upbringing and education in Los Angeles and then his Ph.D. studies at Harvard. He goes on to describe his arrival at Suffolk, his many and varied teaching experiences over the years, his tenure as chair, and his contributions to the English Department’s overall educational approach. Merzlak describes teaching as his vocation and how Suffolk provided an inspiring and sustaining environment for him. He then discusses the authors and courses that he loved to teach, year in and year out, plus memories of the students and colleagues who had meant the most to him over his lengthy career at Suffolk. He also reflection on Suffolk’s evolution in the years leading up to his retirement.https://dc.suffolk.edu/soh/1049/thumbnail.jp
Suffolk University Law School Academic Catalog, 2020-2021
Get PDFThis catalog contains information on academic policies, program requirements, and course descriptions for Suffolk University Law School.https://dc.suffolk.edu/suls-catalogs/1073/thumbnail.jp
Fair Use and Machine Learning
Get PDFThere would be a beaten path to the maker of software that could reliably state whether a use of a copyrighted work was protected as fair use. But applying machine learning to fair use faces considerable hurdles. Fair use has generated hundreds of reported cases, but machine learning works best with examples in greater numbers. More examples may be available, from mining the decision making of web sites, from having humans judge fair use examples just as they label images to teach self-driving cars, and using machine learning itself to generate examples. Beyond the number of examples, the form of the data is more abstract than the concrete examples on which machine learning has succeeded, such as computer vision, viewing recommendations, and even in comparison to machine translation, where the operative unit was the sentence, not a concept that could be distributed across a document. But techniques presently in use do find patterns in data to build more abstract features, and then use the same process to build more abstract features. It may be that such automated processes can provide the conceptual blocks necessary. In addition, tools drawn from knowledge engineering (ironically, the branch of artificial intelligence that of late has been eclipsed by machine learning) may extract concepts from such data as judicial opinions. Such tools would include new methods of knowledge representation and automated tagging. If the data questions are overcome, machine learning provides intriguing possibilities, but also faces challenges from the nature of fair use law. Artificial neural networks have shown formidable performance in classification. Classifying fair use examples raises a number of questions. Fair use law is often considered contradictory, vague, and unpredictable. In computer science terminology, the data is “noisy.” That inconsistency could flummox artificial neural networks, or the networks could disclose consistencies that have eluded commentators. Other algorithms such as nearest neighbor and support vectors could likewise both use and test legal reasoning by analogy. Another approach to machine learning, decision trees, may be simpler than other approaches in some respects, but could work on smaller data sets (addressing one of the data issues above) and provide something that machine learning often lacks: transparency. Decision trees disclose their decision-making process, whereas neural networks, especially deep learning, are opaque black boxes. Finally, unsupervised machine learning could be used to explore fair use case law for patterns, whether they be consistent structures in its jurisprudence, or biases that have played an undisclosed role. Any possible patterns found, however, should be treated as possibilities, pending testing by other means
Listen! Amplifying the Experiences of Black Law School Graduates in 2020
Get PDFLaw students graduating in 2020 faced a number of unusual challenges. However, perhaps no students faced more emotional, psychological, logistical, and financial challenges than Black law school graduates in 2020. In addition to changes in the administration of the bar exam (including the use of technology that struggled to recognize Black faces) and delays in the administration of the exam that led to anxiety and increased financial instability, Black communities were concurrently being disproportionately impacted by the COVID-19 pandemic. The pandemic led to increased care-taking responsibilities for many, concerns over the health of family members, and a lack of quiet and reliable space to study. Black law school graduates already struggling to juggle these challenges were also confronted with a rise in anti-Black police brutality, and the racist words and actions of politicians. As a result of this unprecedented series of stressors, many Black law gradates struggled to focus on studying for the bar, with some choosing to delay or abandon sitting for the bar altogether. Many expressed anger, disappointment, and betrayal at the profession they have worked so hard to enter. This Article summarizes the survey responses of over 120 Black law students who graduated in 2020 and were asked how the COVID pandemic and increased anti-Black violence impacted their health, education, and career aspirations. It seems likely that the impact of 2020 on the presence and wellbeing of Black lawyers in the legal profession will be felt for years to come. As professors, deans, lawyers, and policymakers reexamine the function of the bar exam and confront inequalities in legal education, we need to listen to these graduates’ experiences