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This program profile of the Critical Writing Program at the University of Pennsylvania focuses on how disability came to be a valued term, a structuring philosophy, and a pedagogical touchstone for the program's philosophy, curriculum, and practices. After exploring various challenges involved in addressing the needs of students with disabilities, we provide an overview of our program's efforts to address the needs of students with disabilities. In so doing, we explain how we came to adopt an orientation towards disability that depends for its philosophical force on a return to Derrida's advocacy of the deconstructive notion of "différance." "Différance" seeks to overturn binary thinking, challenge uninterrogated binaries such as abled/disabled and the normate templates that enact and enforce these, replacing them with a relational, fluid, contextual approach.

As technical communication (TC) instructors, it is vital that we continue reimagining our curricula as the field itself is continually reimagined in light of new technologies, genres, workplace practices, and theories--theories such as those from disability studies scholarship. Here, the authors offer an approach to including disability studies in TC curricula through the inclusion of a "critical accessibility case study" (CACS). In explicating the theoretical and practical foundations that support teaching a CACS in TC courses, the authors provide an overview of how TC scholars have productively engaged with disability studies and case studies to question both our curricular content and classroom practices. They offer as an example their "New York City Evacuation CACS," developed for and taught in TC for Health Sciences courses, which demonstrates that critical disability theory can help us better teach distribution and design of technical information and user-based approaches to TC. The conceptual framework of the CACS functions as a strategy for TC instructors to integrate disability studies and attention to disability and accessibility into TC curricula, meeting both ethical calls to do so as well as practical pedagogical goals.

Although attention to disability is becoming more apparent in first-year composition curricula, too often disability is simply "tacked on" to existing courses. Scholars have argued that composition instructors interested in fully integrating a disability studies perspective into their curriculum would do well, instead, to think critically about every aspect of their classroom spaces, the subject matter they teach, and the ways in which they teach it. This can seem, however, like an overwhelming task, even for instructors interested in incorporating a disability studies perspective into their pedagogy. This may be especially challenging for instructors working within standardized composition programs without much flexibility in the curricula they are asked to teach. Using as an example a sample first-year composition curriculum at a large public university, this article explores how a disability studies perspective can be incorporated into a composition classroom in meaningful, productive ways, without altering the curriculum itself. In so doing, the article provides readers with a number of theoretical approaches to disability studies that may be helpful in reconsidering pedagogical strategies in a composition classroom, and also provides readers with suggestions for concrete, practical applications of such reframing strategies within the context of this particular sample curriculum.

High‐throughput environmental sensing technologies are increasingly central to global monitoring of the ecological impacts of human activities. In particular, the recent boom in passive acoustic sensors has provided efficient, noninvasive, and taxonomically broad means to study wildlife populations and communities, and monitor their responses to environmental change. However, until recently, technological costs and constraints have largely confined research in passive acoustic monitoring (PAM) to a handful of taxonomic groups (e.g., bats, cetaceans, birds), often in relatively small‐scale, proof‐of‐concept studies.The arrival of low‐cost, open‐source sensors is now rapidly expanding access to PAM technologies, making it vital to evaluate where these tools can contribute to broader efforts in ecology and biodiversity research. Here, we synthesise and critically assess the current emerging opportunities and challenges for PAM for ecological assessment and monitoring of both species populations and communities.We show that terrestrial and marine PAM applications are advancing rapidly, facilitated by emerging sensor hardware, the application of machine learning innovations to automated wildlife call identification, and work towards developing acoustic biodiversity indicators. However, the broader scope of PAM research remains constrained by limited availability of reference sound libraries and open‐source audio processing tools, especially for the tropics, and lack of clarity around the accuracy, transferability and limitations of many analytical methods.In order to improve possibilities for PAM globally, we emphasise the need for collaborative work to develop standardised survey and analysis protocols, publicly archived sound libraries, multiyear audio datasets, and a more robust theoretical and analytical framework for monitoring vocalising animal communities. [ABSTRACT FROM AUTHOR]

Abstract: To prevent further global declines in biodiversity, identifying and understanding key habitats is crucial for successful conservation strategies. For example, globally, seabird populations are under threat and animal movement data can identify key at‐sea areas and provide valuable information on the state of marine ecosystems. To date, in order to locate these areas, studies have used global positioning system (GPS) to record position and are sometimes combined with time–depth recorder (TDR) devices to identify diving activity associated with foraging, a crucial aspect of at‐sea behaviour. However, the use of additional devices such as TDRs can be expensive, logistically difficult and may adversely affect the animal. Alternatively, behaviours may be resolved from measurements derived from the movement data alone. However, this behavioural analysis frequently lacks validation data for locations predicted as foraging (or other behaviours). Here, we address these issues using a combined GPS and TDR dataset from 108 individuals by training deep learning models to predict diving in European shags, common guillemots and razorbills. We validate our predictions using withheld data, producing quantitative assessment of predictive accuracy. The variables used to train these models are those recorded solely by the GPS device: variation in longitude and latitude, altitude and coverage ratio (proportion of possible fixes acquired within a set window of time). Different combinations of these variables were used to explore the qualities of different models, with the optimum models for all species predicting non‐diving and diving behaviour correctly over 94% and 80% of the time, respectively. We also demonstrate the superior predictive ability of these supervised deep learning models over other commonly used behavioural prediction methods such as hidden Markov models. Mapping these predictions provides useful insights into the foraging activity of a range of seabird species, highlighting important at sea locations. These models have the potential to be used to analyse historic GPS datasets and further our understanding of how environmental changes have affected these seabirds over time. [ABSTRACT FROM AUTHOR]