Communicating to CALD communities about energy: Best practice engagement to connect with digitally excluded groups
Bibliographic record
Abstract
This research examines the critical challenges facing culturally and linguistically diverse (CALD) communities in Australia as they navigate the country’s transition to clean energy. With CALD communities comprising nearly a quarter of Australia’s population, there is growing concern that the shift toward digital communication and complex energy market information is leaving these communities, particularly newly arrived migrants and older people, behind in the energy transition. To understand this challenge, a literature review and interviews with participants from Victorian multicultural and ethnic community groups were conducted to: 1. Engage with CALD community organisations to understand foundational knowledge gaps that are impacting how CALD communities engage with residential energy supply in Australia. 2. Understand the information access needs of newly arrived migrants and older CALD communities 3. Identify examples of how to engage these communities in communications with emphasis on non- digital formats around complex issues in energy markets.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.002 | 0.021 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.019 | 0.004 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".