Translanguaging for more-than-English sustainability transitions
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
Critical sustainability research pays insufficient attention to the need for language justice in action toward sustainable cities. Addressing this gap can increase inclusive action competence in sustainability. Including diverse languages, along with the work that goes into communicating effectively across languages, can counter the disproportionate dominance of English in sustainability. This is an underexamined aspect of the sustainability knowledge-action gap. Language diversity is large and growing in cities and professions pursuing sustainable development. While English is the lingua franca of sustainability science, learners and actors engage in translanguaging or moving across languages to inform their understanding and communication in culturally and personally relevant ways. Recognising the effort that goes into translanguaging and highlighting language-specific entry points to sustainability transition can deepen the meaningfulness of local sustainability efforts. We designed a workshop to engage the translanguaging competencies of interdisciplinary sustainability learners. Results demonstrate that students were able to build shared understanding through different languages and relate the concepts across languages. This was inclusive of cultural values and personally rewarding for participants. The workshop additionally exposed students to sustainability terms in a language foreign to all of them, Finnish. Students were able to relate meanings to a spectrum of sustainability-related actions that were more readily accessible to them than conventional English language action agendas for sustainability. This workshop demonstrates a replicable methodology to increase attention to diverse languages for activating sustainability agendas. The process of translanguaging, moving across languages to communicate and convey meaning, holds unrecognised value for inclusive sustainability action competence.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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