Broken Policies • Broken Communication \nCorrect Messaging in Energy Transition Policies
Bibliographic record
Abstract
This research provides communication tools and techniques to assist policy makers. It uses the idea that public acceptance of a policy is parallel to consumer acceptance of a product. By doing so the research attempts to bring market knowledge to bear on public discourse around policy yields. It is through this knowledge that insight about more effective communication tools, techniques and approaches to ensure acceptance of sustainable energy transition policies is provided. The research uses two case studies to analyze the above relationships. First, it takes a closer look at the Alberta Climate Leadership plan. An adapted MLP framework is applied to the plan, with a focus on the ability of communication to assist with energy transition. A media analysis and public survey are also utilized in order to identify key barriers in the acceptance of the policy, with a focus on barriers based of language and communication. The second case study is an emersion into a global brand. Through in-depth interviews and observations, key brand strategy tools were identified. These were the importance of emotions, threat, and stories. These brand tools were applied to the policy case study and by doing so provided tools for removing policy acceptance barriers through communication.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".