Mapping Dialectal Variation Using the Algonquian Linguistic Atlas
Bibliographic record
Abstract
The Algonquian Linguistic Atlas (URL: www.ling-atlas.ca), a collaborative project started in 2005 (Co-author et al. 2005), is an online multimedia linguistic atlas of Algonquian languages across Canada. It includes data primarily from the Cree-Innu- Naskapi continuum, but also from Mi’kmaw, Ojibwe, Blackfoot, Algonquin, Mitchif, Oji-Cree, and Maliseet, collected from 2002 to the present, including 42 communities from Alberta to Labrador. In this multimedia presentation we show how data previously gathered for the Atlas for pedagogical purposes can be (re-)used to for a bottom-up linguistic study of dialectal boundaries and degree of relatedness of neighbouring languages. The questionnaire includes the elicitation of single words and phrases categorized into 21 themes, such as greetings, kinship terms, days of the week, weather, orders and requests, and hunting. Although the data collected was initially only conversation-based, the questionnaire was later enriched to elicitate and verify patterns of dialectal variation. Using this data and previous smaller-scale dialectal work as a reference, (MacKenzie (1980), Valentine (1995), Béland (1979) and Drapeau (1979)), we identified 114 distinct variable phonological, lexical, grammatical, syntactic and semantic features which were analyzed for each community across the country. The realizations or variants for each feature were coded in each community, creating isogloss maps based on data collected, to be available via the online interface. These individual feature maps are then compared and compiled in R (R Core Team, 2013; Wikham, H. 2009; Wikham, H. et. al, 2016) to reveal the isogloss bundles drawn from the Atlas data. We will demonstrate the usefulness of this bottom-up approach by discussing a few isogloss bundles found. First, an isogloss bundle is confirmed between dialects of Cree-Innu-Naskapi which undergo palatalization, versus those who do not (also attested in MacKenzie 1980). Our findings also show an isogloss bundle at the Manitoba-Ontario border of Canada, where a number of realizations cluster together west of the border versus different realizations to the east. Lastly, while Drapeau (1979) and MacKenzie (1980) noted that the recent sound change of /ʃ/ to /h/ primarily affected n- and l-speakers of Innu, data from the Atlas shows that this change also applies to Oji-Cree speakers, a more Western n-dialect, previously unattested in dialectal work. This research project illustrates how digitized resources designed as pedagogical and lexicological tools can also serve as useful tools for linguistic analysis. Our findings can help deepen the understanding of Algonquian dialectal variation while contributing to the efforts of communities working towards the revitalization and promotion of their languages. References Béland. 1978 Atikamekw Morphology and Lexicon. Ph. D. Thesis, University of California, Berkeley. Drapeau, Lynn. 1979. Aspects de la morphologie du nom en montagnais. Ph.D. Thesis, Universite de Montréal. Haas, Walter. 2010. A study on areal diffusion. In: Language and Space: An International Handbook on Linguistic variation. Volume 1: Theories and Methods. Peter Auer and Jürgen Erich Schmidt, eds. De Gruyter Mouton, Germany. Horden, John. 1881. A Grammar of the Cree Language, As Spoken by the Cree Indians of North America. London: Society for Promoting Christian Knowledge. Howse, James. 1844. A Grammar of the Cree Language. London: J.G.F. & J. Rivington. Co-author (dir.), Marguerite MacKenzie, Co-author, J. Randolph Valentine & Arok Wolvengrey (co-dir.). 2005-present. The Algonquian Linguistic Atlas. Available at: http://www.atlas-ling.ca/#. Last accessed: May 16, 2016. Lacombe, Albert. 1874. Grammaire de la langue des Cris. Montreal. MacKenzie, Marguerie. 1980. Towards a Dialectology of Cree-Montagnais-Naskapi. Doctor of philosophy dissertation. University of Toronto. Pentland, David H. 1979. Algonquian Historical Phonology. Ph. D. Thesis, University of Toronto. R Core Team (2013). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL: http://www.R- project.org/. Valentine, J. Randolph. 1995. Ojibwe Dialect Relations: Lexical Maps. Wickham, Hadley; Romain François; RStudio. 2016. Dlyr: A Grammar of Data Manipulation. MIT. URL: https://github.com/hadley/dplyr Wickham, Hadley. 2009. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".