Moral Imagination, Ecological Crisis, and the Recalcitrance of the Other

This dissertation critically examines the imaginative habits of a strand of environmentalism characterized by its preoccupation with transforming the worldviews of other people. I argue that these would-be worldview changers are animated by anxiety over the existence of their ethico-political opponents, whom they cast as mere barriers to solving ecological problems. Employing a methodology inherited from ordinary language philosophers, the project seeks to augment the imaginations of such environmentalists, freeing them from a narrow focus on worldview change and supporting them to imagine a future on a damaged planet where other people do not disappear through conversion but require negotiation. The argument unfolds in three stages; the first (Chapters 1 and 2) is diagnostic and critical. I argue that a particular picture of environmentalism’s other as such, a figure I call the ecological other, constrains the imaginations of eco-conversionists to the modality of worldview change. In this picture, the ecological other is figured as transparent despite their heterogeneity and insignificant on moral matters concerning the nonhuman: a familiar and inconsequential stranger. I also argue that multiple strategic and moral problems attend this preoccupation with worldview change, ranging from the alienation of potential allies to allotting the other a merely impedimental role in one’s thought and action. To expand the eco-conversionist imagination beyond its focus on worldview change, I describe another conception of the other that illuminates additional relational modes. Stage two (Chapters 3 and 4) develops that alternative picture by considering how others’ perspectives can be opaque to an onlooker and how the others of environmentalism can prove strategically, epistemically, and ethically significant on nonhuman matters. Those examinations suggest the image of the other as a genuinely strange stranger, who may bear gifts. Stage three describes further modalities of other-relation that come into view when we contemplate this alternative conception of the ecological other. In Chapter 5, I suggest that this conception invites the idea of trying to dissolve another’s opacity, a labor I call apprenticeship. That relational mode, in turn, leads me to consider the ways in which such efforts can go wrong, including that others can refuse to take us on as apprentices. I illustrate this possibility by considering Indigenous American refusals to collaborate with settlers, including environmentalists. That efforts to dissolve another’s opacity can fail in these ways suggests a further relational possibility, namely, that one might learn to live with another’s opacity. In Chapter 6, I argue that the picture of the other as genuinely other also suggests the relational modality of revisiting our preconceptions of others, a possibility I call re-reading. I illustrate this possibility vis-à-vis the figure of one of Western environmentalism’s repugnant others: the conservative Christian anti-environmentalist. I re-read this other by examining a collection of hunting and fishing devotionals authored by American Evangelicals and marketed to a sympathetic audience. I argue that these objects parochialize the image of this opponent as narrowly unconcerned with the nonhuman and that re-reading practices are morally and politically valuable

A Forward Analytic Model of Neutron Time-of-Flight Signals with Single Elastic Scattering and Beamline Attenuation for Inferring Ion Temperatures from MagLIF Experiments

A forward analytic model is required to rapidly simulate the neutron time-of-flight (nToF) signals that result from magnetized liner inertial fusion (MagLIF) experiments at Sandia’s Z Pulsed Power Facility. Various experimental parameters, such as the burn-weighted fuel-ion temperature and liner areal density, determine the shape of the nToF signal and are important for characterizing any given MagLIF experiment. Extracting these parameters from measured nToF signals requires an appropriate analytic model that includes the primary DD neutron peak, once-scattered neutrons in the beryllium liner of the MagLIF target, and direct beamline attenuation. Mathematical expressions for this model were derived from the general geometry time- and energy-dependent neutron transport equation with anisotropic scattering. Assumptions consistent with the time-of-flight technique were used to simplify this linear Boltzmann transport equation into a more tractable form. Models of the un-collided and once-collided neutron scalar fluxes were developed for one of the five nToF detector locations at the Z Machine. Numerical results from these models were produced for a representative MagLIF problem and found to be in good agreement with similar radiation transport simulations. Twenty experimental MagLIF data sets were analyzed using the forward models, which were determined to only be sensitive to the ion temperature. The results of this work were found to be in good agreement with values obtained separately using other low and high fidelity models

What Does It Take? Deciphering Performance Indicators of NFL Running Backs through the Examination of Collegiate Performance and NFL Combine Results

This research uses a linear regression model to investigate the relationship between prospective NFL running backs’ NCAA FBS football statistics, NFL Combine measureables, and realized performance in the NFL as evaluated by Pro Football Focus. We observe 435 player-seasons from 2007-2014. The model suggests that collegiate conference affiliation, collegiate touchdowns, and NFL team passing strength are positively associated with NFL running back performance at statistically significant levels. Conference affiliation has the most substantial effect. NFL talent evaluators must appreciate that context is king when evaluating potential, and that pure stats are only a small piece of the puzzle

Association rule mining to identify potential under-coding of conditions in the problem list in primary care electronic medical records

Introduction The problem list of a patient’s primary care electronic medical record (EMR) generally reflects their important medical conditions. We will use association rule mining to assess between-provider and between-clinic variation in the coding of select conditions in the EMR problem list, in order to identify possible under-coding outliers. Objectives and Approach EMR data from participating clinics in the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) will be used, with a focus on three commonly-occurring conditions (hypertension, diabetes, and depression). Association rule mining will be used to develop association rules between these conditions and other clinical information available in the EMR, such as other diagnoses in the problem list, billing codes, medications, and laboratory results (e.g., a rule of “diabetic medication→diabetes” indicates that patients prescribed a diabetic medication are likely to have diabetes in the problem list). Under-coding outliers at the provider and clinic levels will be identified by comparing rule enforcement. Results Results from this work in progress will be presented at the conference. An estimated 270 clinics, 1340 providers, and 1.8 million patients will be included from the CPCSSN database. Rule ‘confidence’ will be used to identify outliers; the confidence of a rule X→Y is the proportion of individuals with X who also have Y (Pr(Y|X)). For example, we may find that on average 80% of patients prescribed a diabetic medication will also have a diagnosis of diabetes in the problem list (average confidence of 80%), but an outlier clinic may have a confidence of 40%; this low rule confidence may indicate under-coding of diabetes in the problem list. Confounding by patient demographics (e.g., age, sex, urban/rural) will be assessed and adjusted for, if necessary. Conclusion/Implications This work examines a novel method to identify potential under-coding in the EMR problem list. Providers/clinics could use this information to update patients’ problem list or inform quality improvement interventions. Researchers using primary care EMR data need to be aware of potential under-coding and take steps to mitigate the effects

The Grizzly, February 7, 2013

Trustees Plan the Future of Ursinus • Forum Changes Time, Place • Graduation Speakers Selected • Writing Center to Expand Resources • New Exhibit at Berman Museum of Art • Summer Internship Profile • Students Set to Perform Noises Off on February 20 • Students Discuss Queer Life on Liberal Arts Campus • Opinion: U.S. Gun Legislation Needs to be Amended; Our Reliance on Technology is Changing the Way we Think • February 1 Banner Day for Spring Athletes • Swimming Sweeps WAChttps://digitalcommons.ursinus.edu/grizzlynews/1874/thumbnail.jp

Coherent Coupling of a Diamond Tin-Vacancy Center to a Tunable Open Microcavity

Efficient coupling of optically active qubits to optical cavities is a key challenge for solid-state-based quantum optics experiments and future quantum technologies. Here we present a quantum photonic interface based on a single Tin-Vacancy center in a micrometer-thin diamond membrane coupled to a tunable open microcavity. We use the full tunability of the microcavity to selectively address individual Tin-Vacancy centers within the cavity mode volume. Purcell enhancement of the Tin-Vacancy center optical transition is evidenced both by optical excited state lifetime reduction and by optical linewidth broadening. As the emitter selectively reflects the single-photon component of the incident light, the coupled emitter-cavity system exhibits strong quantum nonlinear behavior. On resonance, we observe a transmission dip of 50 % for low incident photon number per Purcell-reduced excited state lifetime, while the dip disappears as the emitter is saturated with higher photon number. Moreover, we demonstrate that the emitter strongly modifies the photon statistics of the transmitted light by observing photon bunching. This work establishes a versatile and tunable platform for advanced quantum optics experiments and proof-of-principle demonstrations towards quantum networking with solid-state qubits.Comment: 15 pages, 12 figure

Reporting of Model Performance and Statistical Methods in Studies That Use Machine Learning to Develop Clinical Prediction Models: Protocol for a Systematic Review

BACKGROUND: With the growing excitement of the potential benefits of using machine learning and artificial intelligence in medicine, the number of published clinical prediction models that use these approaches has increased. However, there is evidence (albeit limited) that suggests that the reporting of machine learning-specific aspects in these studies is poor. Further, there are no reviews assessing the reporting quality or broadly accepted reporting guidelines for these aspects. OBJECTIVE: This paper presents the protocol for a systematic review that will assess the reporting quality of machine learning-specific aspects in studies that use machine learning to develop clinical prediction models. METHODS: We will include studies that use a supervised machine learning algorithm to develop a prediction model for use in clinical practice (ie, for diagnosis or prognosis of a condition or identification of candidates for health care interventions). We will search MEDLINE for studies published in 2019, pseudorandomly sort the records, and screen until we obtain 100 studies that meet our inclusion criteria. We will assess reporting quality with a novel checklist developed in parallel with this review, which includes content derived from existing reporting guidelines, textbooks, and consultations with experts. The checklist will cover 4 key areas where the reporting of machine learning studies is unique: modelling steps (order and data used for each step), model performance (eg, reporting the performance of each model compared), statistical methods (eg, describing the tuning approach), and presentation of models (eg, specifying the predictors that contributed to the final model). RESULTS: We completed data analysis in August 2021 and are writing the manuscript. We expect to submit the results to a peer-reviewed journal in early 2022. CONCLUSIONS: This review will contribute to more standardized and complete reporting in the field by identifying areas where reporting is poor and can be improved. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CRD42020206167; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=206167. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/30956