Bibliographic record
Abstract
Abstract Haas's (1944) typology of nonreferential gender indexicality attested three basic varieties: speaker indexing, addressee indexing, and ‘mixed’ (or relational) speaker-addressee gender indexing. In an earlier publication inLanguage in Societythis author adopted the same framework for the treatment of a large sample of cases of categorical gender indexicality. However, subsequent review of cases where gender indexicality seemingly interacts with sex-based semantic gender suggests that Haas' typology is incomplete. A relational speaker-referent indexing type is proposed. Focusing on gender indexicality in Chiquitano (Bolivia) and Yanyuwa (Australia), the author argues that these cases have been erroneously treated as systems in which speaker gender is indexed in the denotation of referent gender. It is shown that a more parsimonious analysis can account for these cases by means of a single purely pragmatic gender feature distributed over a relational speaker-referent indexical focus. (Gender, indexicality, deixis)*
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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 | 0.010 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".