The Discourse of Voicemail

This paper attempts to determine to what degree voicemail messages can be considered a discourse genre – that is, to what degree and in what ways they appear to be uniform across speakers. Thirty-seven voice messages were recorded from the cellular phones of three University of Michigan students. The messages were analyzed in terms of their overall structure, the discursive functions that were executed therein, and the specific words, phrases and prosodic strategies that were used to execute certain functions. The messages were found to have highly uniform openings and closings, and the message bodies were found to reduce to a small set of discursive functions. In addition, certain words, phrases and devices appeared frequently and in predictable locations within the messages. It is concluded that voicemail message-leaving is a highly structured act governed by conventions that arise both from face-to-face conversation and from the specific constraints of the medium

Counterfactual Mean-variance Optimization

We study a new class of estimands in causal inference, which are the solutions to a stochastic nonlinear optimization problem that in general cannot be obtained in closed form. The optimization problem describes the counterfactual state of a system after an intervention, and the solutions represent the optimal decisions in that counterfactual state. In particular, we develop a counterfactual mean-variance optimization approach, which can be used for optimal allocation of resources after an intervention. We propose a doubly-robust nonparametric estimator for the optimal solution of the counterfactual mean-variance program. We go on to analyze rates of convergence and provide a closed-form expression for the asymptotic distribution of our estimator. Our analysis shows that the proposed estimator is robust against nuisance model misspecification, and can attain fast $\sqrt{n}$ rates with tractable inference even when using nonparametric methods. This result is applicable to general nonlinear optimization problems subject to linear constraints whose coefficients are unknown and must be estimated. In this way, our findings contribute to the literature in optimization as well as causal inference. We further discuss the problem of calibrating our counterfactual covariance estimator to improve the finite-sample properties of our proposed optimal solution estimators. Finally, we evaluate our methods via simulation, and apply them to problems in healthcare policy and portfolio construction

Flexible Group Fairness Metrics for Survival Analysis

Algorithmic fairness is an increasingly important field concerned with detecting and mitigating biases in machine learning models. There has been a wealth of literature for algorithmic fairness in regression and classification however there has been little exploration of the field for survival analysis. Survival analysis is the prediction task in which one attempts to predict the probability of an event occurring over time. Survival predictions are particularly important in sensitive settings such as when utilising machine learning for diagnosis and prognosis of patients. In this paper we explore how to utilise existing survival metrics to measure bias with group fairness metrics. We explore this in an empirical experiment with 29 survival datasets and 8 measures. We find that measures of discrimination are able to capture bias well whereas there is less clarity with measures of calibration and scoring rules. We suggest further areas for research including prediction-based fairness metrics for distribution predictions.Comment: Accepted in DSHealth 2022 (Workshop on Applied Data Science for Healthcare

Filtering Tweets for Social Unrest

Since the events of the Arab Spring, there has been increased interest in using social media to anticipate social unrest. While efforts have been made toward automated unrest prediction, we focus on filtering the vast volume of tweets to identify tweets relevant to unrest, which can be provided to downstream users for further analysis. We train a supervised classifier that is able to label Arabic language tweets as relevant to unrest with high reliability. We examine the relationship between training data size and performance and investigate ways to optimize the model building process while minimizing cost. We also explore how confidence thresholds can be set to achieve desired levels of performance

Evidence for language transfer leading to a perceptual advantage for non-native listeners

Phonological transfer from the native language is a common problem for non-native speakers that has repeatedly been shown to result in perceptual deficits vis-a-vis native speakers. It was hypothesized, however, that transfer could help, rather than hurt, if it resulted in a beneficial bias. Due to differences in pronunciation norms between Korean and English, Koreans in the U.S. were predicted to be better than Americans at perceiving unreleased stops--not only in their native language (Korean) but also in their non-native language (English). In three experiments, Koreans were found to be significantly more accurate than Americans at identifying unreleased stops in Korean, at identifying unreleased stops in English, and at discriminating between the presence and absence of an unreleased stop in English. Taken together, these results suggest that cross-linguistic transfer is capable of boosting speech perception by non-natives beyond native levels

Vascular plant extinction in the continental United States and Canada.

Extinction rates are expected to increase during the Anthropocene. Current extinction rates of plants and many animals remain unknown. We quantified extinctions among the vascular flora of the continental United States and Canada since European settlement. We compiled data on apparently extinct species by querying plant conservation databases, searching the literature, and vetting the resulting list with botanical experts. Because taxonomic opinion varies widely, we developed an index of taxonomic uncertainty (ITU). The ITU ranges from A to F, with A indicating unanimous taxonomic recognition and F indicating taxonomic recognition by only a single author. The ITU allowed us to rigorously evaluate extinction rates. Our data suggest that 51 species and 14 infraspecific taxa, representing 33 families and 49 genera of vascular plants, have become extinct in our study area since European settlement. Seven of these taxa exist in cultivation but are extinct in the wild. Most extinctions occurred in the west, but this outcome may reflect the timing of botanical exploration relative to settlement. Sixty-four percent of extinct plants were single-site endemics, and many occurred outside recognized biodiversity hotspots. Given the paucity of plant surveys in many areas, particularly prior to European settlement, the actual extinction rate of vascular plants is undoubtedly much higher than indicated here