The Written Questionnaire as a Sociolinguistic Data Gathering Tool
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
Self-reports in linguistic study, which were central to the dialect surveys of the twentieth century, have, by and large, been relegated to the sidelines by more advanced sociolinguistic techniques in recent years. This article probes into the validity of written self-report surveys in relation to the fieldwork method for Vancouver, British Columbia. Confirming Chambers’s general findings of equivalence, it produces insights into the preferred length of written questionnaires and offers recommendations as to question type. The present article also compares the written questionnaire results to acoustically analyzed recorded data for yod-dropping and the low-back vowels before /r/, identifying linguistic items that correlate well with results from self-reports and those that fail to produce reliable results because of ongoing linguistic change or reindexicalization in the case of yod-dropping. Overall, written self-report surveys are found to be highly reliable data gathering tools if certain factors are kept in mind.
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 | 0.004 | 0.501 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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