1,720,979 research outputs found
Guidelines for Data Annotation
No full textIncluded here are a coding manual and supplementary examples of gesture forms (in still images and video recordings) that informed the coding of the first author (Kate Mesh) and four project reliability coders
Replication Data for Inter-Rater Reliability Measures
No full textIncluded here are a dataset with coding from the study author (Kate Mesh) and four reliability coders: Marcus Martinez and Phoebe Minz (undergraduate research assistants at The University of Texas at Austin), Salma Halabi and Yara Abu-Roker (undergraduate research assistants at the University of Haifa, Haifa, Israel). Each reliability coder worked with 10% of the total dataset, and each reliability coder's work was individually compared with that of the study author. For all author-reliability coder pairs, a measure of inter-rater agreement and a Cohen's Kappa score were computed using R version 3.6.1 (R Core Team, 2019), with the package, irr (Gamer, Lemon, Fellows & Singh, 2019). An R script is attached for the purposes of replication.
R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
Matthias Gamer, Jim Lemon, Ian Fellows and Puspendra Singh. (2019). irr: Various Coefficients of Interrater Reliability and Agreement. R package version 0.84.1. https://CRAN.R-project.org/package=ir
Replication Data for Statistical Analysis
No full textIncluded here is a dataset with gesture form coding from the study author (Kate Mesh). Statistical analysis of the dataset was performed using R version 3.6.1 (R Core Team, 2019), with the package, lmer (Bates, Maechler, Bolcher & Walker, 2015). An R script is attached for the purposes of replication.
R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
Douglas Bates, Martin Maechler, Ben Bolker, Steve Walker (2015). Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software, 67(1), 1-48. doi:10.18637/jss.v067.i01
Selected video examples for the dissertation, Points of Comparison: What Indicating Gestures tell us About the Origins of Signs in San Juan Quiahije Chatino Sign Language
No full textVideo clips corresponding to examples in the dissertation, Points of Comparison: What Indicating Gestures tell us About the Origins of Signs in San Juan Quiahije Chatino Sign Languag
Metalinguistic interview data for the dissertation, Points of Comparison: What Indicating Gestures tell us About the Origins of Signs in San Juan Quiahije Chatino Sign Language
No full textMetalinguistic interview data for: Points of Comparison: What Indicating Gestures tell us About the Origins of Signs in San Juan Quiahije Chatino Sign Languag
Local environment interview data for the dissertation, Points of Comparison: What Indicating Gestures tell us About the Origins of Signs in San Juan Quiahije Chatino Sign Language
No full textMetalinguistic interview data for Points of Comparison: What Indicating Gestures tell us About the Origins of Signs in San Juan Quiahije Chatino Sign Languag
Video Examples and Replication Data for: Negation in San Juan Quiahije Chatino Sign Language
No full textThis dataverse contains a coding manual and a dataset of annotated language used for a study titled, Negation in San Juan Quiahije Chatino Sign Language. In the corresponding paper, we analyze the use of negative emblems in a sign language used in an indigenous Chatino community of Oaxaca. To perform the analysis, we identified tokens of negative manual emblems in over 5 hours of video recorded interaction. We then coded the form, function, and syntactic distribution of each token. The resulting set of annotations is deposited here. The original set of video recordings is deposited with the Endangered Languages Archive in two deposits:
Hou, L, and Mesh, K. (2018). Documenting Chatino Sign Language. London: SOAS, Endangered Languages Archive. Access: Public. Deposit ID 0355.
Mesh, K. (2018). Gesture, Speech and Sign in Chatino Communities. London: SOAS, Endangered Languages Archive. Access: Public. Deposit ID 0459.
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Replication data for: Effects of scale on multimodal deixis
No full textArchived here are supplementary materials for the paper, Effects of scale on multimodal deixis. These include guidelines for video annotation, as well as datasets with gesture form coding from the study's first author (Kate Mesh) and reliability coder (Nicolas Femia). Statistical analysis of the dataset coded by the first author was performed by Joost van de Weijier and Kate Mesh using R version 3.6.1 (R Core Team, 2019), with the packages lmer (Bates, et al., 2015) and multcomp (Hothorn et al., 2008). An R script is included for the purposes of replication.
R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
Douglas Bates, Martin Maechler, Ben Bolker, Steve Walker (2015). Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software, 67(1), 1-48. doi:10.18637/jss.v067.i01. (2020-04-15)
Torsten Hothorn, Frank Bretz and Peter Westfall (2008). Simultaneous Inference in General Parametric Models. Biometrical Journal 50(3), 346-363
Initial person reference in providence island sign language
No full textWhen referring to non-present entities, speakers and signers can select from a range of different strategies to create expressions that range from extremely concise to highly elaborate. This design of referring expressions is based partly on the availability of contextual information that can aid addressee understanding. In the small signing community of Providence Island, signers' heavy reliance on extra-linguistic information has led to their language being labelled as context-dependent (Washabaugh, de Santis & Woodward 1978). This study investigates the semiotic strategies that deaf signers in Providence Island use for referring, and examines how signers optimise specificity and minimise ambiguity by drawing on shared context. We examined first introductions to non-present people in spontaneous dyadic conversations between deaf signers and analysed the semiotic strategies used. We found that signers built referring expressions using the same strategies found in other sign languages, yet designed expressions that made use of contextual knowledge shared through community membership, such as geography, local spoken languages and traits of fellow islanders. Our signers also used strategies described as unusual or unattested in other sign languages, such as unframed constructed action sequences and stand-alone mouthings. This study deepens our understanding of context dependence by providing examples of how context is drawn upon by communities with high degrees of shared knowledge. Our results call into question the classification of sign languages as context-dependent and highlights the differences in data collection across communities and the resulting limitations of cross-linguistic comparisons
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