Bibliographic record
Abstract
This thesis investigates changes associated with the ergative morphosyntactic alignment of the Inuit language. All these changes have been argued to signal an alignment shift from ergative to accusative, though none of them has ever been confirmed with detailed quantitative evidence. The most important change involves the rise of the antipassive construction in Inuktitut dialects at the expense of the ergative construction as the new default transitive construction (see Johns 1999, 2001a, 2001b, 2006, 2017; Spreng 2005; Carrier 2012, 2017; Yuan 2018). Other reported changes are 1) the elimination of overt transitive objects in the most innovative varieties, which would make the ergative construction a ‘marked’ transitive construction (see Johns 2017; Yuan 2018), and 2) the loss of the ergative case on transitive subjects in favor the absolutive case, which also marks intransitive subjects (see Tersis 2004; Langgård 2009; Carrier 2012). Using a variationist sociolinguistic approach to analyze data from North Baffin Inuktitut and a formal syntactic one to interpret the results, this study is the first to provide statistical evidence confirming that the ergative construction and the ergative case have been used progressively less and that they correlate with each other. I also posit that the general ongoing alignment change from ergative to accusative was first initiated by a neutralization in transitive subject number agreement, and that a series of changes has then successively triggered one another. Building on Brook (2018), I thus argue that these distinct changes constitute increasingly bigger envelopes of variation nested in one another and have in turn triggered one another after reaching a certain level of completion. One clear theoretical implication of these successive changes affecting distinct forms that display the traditional ergative alignment of the Inuit language is that ergativity is not a single concept but a macroset of many different properties (e.g., Dixon 1994; Johns 2000; Deal 2015a; Haig 2017).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 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; both teacher heads agree on what is shown here.
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".