Turn-taking in the interactive Linguistic Landscape
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 Building on Linguistic Landscape (LL) research that highlights its interactivity, we examine how interaction is a crucial element in the creation of meaning in the LL. Our analysis draws on the concept of turn-taking from conversation analysis, in applying the concept of turn , i.e. individual interactants’ contributions to conversation, and introducing its counterpart in the LL. Pairing this with the principles of geosemiotics and Ethnographic Linguistic Landscape Analysis (ELLA), we demonstrate that LLs can consist of interlinked semiotic turns that proceed similarly to turns of a conversation. Combining turn-taking, geosemiotics and ELLA encourages us to go beyond the fixation of ‘top-down’ vs. ‘bottom-up’ and ‘transgressive’ processes. Not only does the LL hold an ever-present possibility of an interactive response but we show that actors attend to the turn-taking mechanism that includes consistent approaches to dealing with discernible interactants, taking turns, and turn-design.
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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 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