Research Note: Speaker-referent gender indexicality
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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 in Language in Society this 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)*
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 it