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This study examines the question of how the feedback of peers and teachers on a collaboratively written student text, mediated by track changes and commenting functions in Microsoft (MS) Word, can act as a form of socialization into an academic or professional discipline. It focusses on a collaboratively written legal memorandum, authored by students of law engaged in the practice of 'mooting', i.e. the conduct of mock trials, an activity which requires the development of persuasive legal arguments, both in written and spoken form. This article reports on an ethnographic study of the language socialization observed in a team of law students in Hong Kong, as they went about writing a memorandum for a high-stakes, global arbitration mooting competition. This team was observed over a period of approximately eight months, the first three of which were dedicated to the writing of a 35-page memorandum. The team produced a total of 12 drafts of this memorandum. These drafts were reviewed by the students themselves and the legal academic tutors responsible for training the team, with feedback recorded in MS Word. This article presents a multiple case study of participants in the writing process, noting coaching, peer mentoring and editing roles adopted. The analysis shows how the digitally mediated collaborative writing process supported the socialization of students into the disciplinary culture of the law. The analysis identifies socializing feedback on research process, disciplinary content, discourse and lexico-grammar, and also finds that socializing functions were performed by both experts and novices in the community of practice.

Introduction. La prescription sociale est une approche holistique et collaborative qui vise à aider les individus à avoir accès aux mesures de soutien et aux services communautaires nécessaires pour combler leurs besoins sociaux non médicaux. Cette étude visait à évaluer les besoins et les priorités des aînés canadiens (55 ans et plus), en portant une attention particulière à l'optimisation des programmes de prescription sociale à l'intention des personnes qui sont systémiquement défavorisées et socialement marginalisées. Méthodologie. Des groupes de discussion semi-structurés (N = 10 groupes, 43 participants) ont été organisés en ligne sur Zoom avec des participants de l'ensemble du Canada. La transcription des données et l'analyse thématique ont été réalisées à l'aide du logiciel NVivo. Les analyses s'appuient sur la théorie de l'autodétermination. Résultats. D'après nos résultats, les aînés souhaitent avoir accès à des programmes de prescription sociale qui respectent leur capacité à maintenir leur autonomie et leur indépendance; qui favorisent le développement de liens et d'un sentiment d'appartenance; qui sont fondés sur la confiance et l'établissement de relations solides dans les interactions avec les fournisseurs et les agents de liaison communautaires et qui donnent la priorité à la personne, personnalisant ainsi la prescription sociale en fonction des besoins spécifiques de chacun. Conclusion. Les programmes de prescription sociale doivent être fondés sur les valeurs des aînés. Alors que des travaux sont actuellement en cours pour formaliser et étendre la prescription sociale au Canada, la personnalisation de ces programmes en fonction de la situation, des besoins et des priorités spécifiques des participants devrait être une priorité majeure. [ABSTRACT FROM AUTHOR]

Introduction: Social prescribing (SP) is a holistic and collaborative approach to help individuals access community-based supports and services for their nonmedical social needs. The aim of this study was to assess the needs and priorities of Canadian older adults (aged 55 years and older), with a focus on optimizing SP programs for those who are systemically disadvantaged and socially marginalized. Methods: Semistructured focus groups (N = 10 groups, 43 participants) were conducted online via Zoom with participants from across Canada. Data transcription and thematic analysis were completed in NVivo. Analyses were informed by self-determination theory. Results: Our results suggest that older adults desire SP programs that respect their ability to maintain their autonomy and independence, aid and facilitate the development of connectedness and belonging, are built on a foundation of trust and relationship-building in interactions with providers and link workers, and prioritize the person and thus personalize SP to the unique needs of each individual. Conclusion: SP programs should be informed by the values of older adults. As work is currently underway to formalize and scale SP in Canada, personalizing these programs to the unique circumstances, needs and priorities of participants should be a top priority. [ABSTRACT FROM AUTHOR]

Implied volatility is known to have a string structure (smile curve) for a given time to maturity and can be captured by the B-spline. The parameters characterizing the curves can change over time, which complicates the modeling of the implied volatility surface. Although machine learning models could improve the in-sample fitting, they ignore the structure in common over time and might have poor prediction power. In response to these challenges, we propose a two-step procedure to model the dynamic implied volatility surface (IVS). In the first step, we construct the bivariate tensor-product B-spline (BTPB) basis to approximate cross-sectional structures, under which the surface can be represented by a vector of coefficients. In the second step, we allow for the time-dependent coefficients and model the dynamic coefficients with the tree-based method to provide more flexibility. We show that our approach has better performance than the traditional linear models (parametric models) and the tree-based machine learning methods (nonparametric models). The simulation study confirms that the tensor-product B-spline is able to capture the classical parametric model for IVS given different sample sizes and signal-to-noise ratios. The empirical study shows that our two-step approach outperforms the traditional parametric benchmark, nonparametric benchmark, and parametric benchmark with time-varying coefficients in predicting IVS for the S&P 500 index options in the US market. [ABSTRACT FROM AUTHOR]

Long-term environmental monitoring surveys are designed to achieve a desired precision (measured by variance) of resource conditions based on natural variability information. Over time, increases in resource variability and in data use to address issues focused on small areas with limited sample sizes require bolstering of attainable precision. It is often prohibitive to do this by increasing sampling effort. In cases with spatially overlapping monitoring surveys, composite estimation offers a statistical way to obtain a precision-weighted combination of survey estimates to provide improved population estimates (more accurate) with improved precisions (lower variances). We present a composite estimator for overlapping surveys, a summary of compositing procedures, and a case study to illustrate the procedures and benefits of composite estimation. The study uses the two terrestrial monitoring surveys administered by the Bureau of Land Management (BLM) that entirely overlap. Using 2015–18 data and 13 land-health indicators, we obtained and compared survey and composite indicator estimates of percent area meeting land-health standards for sagebrush communities in Wyoming's Greater Sage-Grouse (Centrocercus urophasianus) Core and NonCore conservation areas on BLM-managed lands. We statistically assessed differences in indicator estimates between the conservation areas using composite estimates and estimates of the two surveys individually. We found composite variance to be about six to 24 units lower than 37% of the survey variances and composite estimates to differ by about six to 10 percentage points from six survey estimates. The composite improvements resulted in finding 11 indicators to statistically differ (p <0.05) between the conservation areas compared to only six and seven indicators for the individual surveys. Overall, we found composite estimation to be an efficient and useful option for improving environmental monitoring information where two surveys entirely overlap and suggest how this estimation method could be beneficial where environmental surveys partially overlap and in small area applications. [ABSTRACT FROM AUTHOR]