Attitudes towards varied inclusive language use in Spanish on Twitter
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
Research into gender-inclusive language in Spanish has demonstrated that inclusive language generally appears in four forms: doublets, -@, -x, and -e. There is little research on language attitudes towards the use of gender-inclusive language in Spanish, although studies exist for other languages. The present study compiled a corpus of published tweets that contained the markers -@, -x, and -e. Based on this data, hypothetical tweets were constructed that fell into four different categories, corresponding to the author of the tweet: business, personal, academic, and political. These hypothetical tweets were built into an attitudes survey that was distributed on Twitter. Findings indicate that language attitudes for each type of inclusive marker and category of tweet are generally positive. Statistical analysis indicates a significant relationship between gender identity and attitudes towards the use of inclusive language in the political category.
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 | 0.001 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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