Towards a new economic paradigm : exploring mental models and message framing effects about ecological economics
Bibliographic record
Abstract
The transition to a sustainable economic paradigm may be one of the most important issues of our times. This study contributes to the effective communication of ecological economics, by: 1) identifying mental models on people’s perceptions about economic growth and the environment, 2) exploring the prevalence of expansionist and ecological attitudes, and segmenting the audience based on these attitudes, and 3) exploring the effects of different messages (about the transition to economies not centered on growth) on people’s thoughts, emotions and attitudes. Sixty interviews and 1,250 online surveys were carried out in British Columbia and Canada, respectively. Data were analysed with NVivo 10, IBM SPSS Statistics 23 and Latent Gold 5.1. Based on the interviews, five mental models were described. These sat in a spectrum of views anchored to an expansionist or to an ecological worldview. The most expansionist views (Cluster A) expressed great faith in indefinite economic growth and human ingenuity. The most ecological perspectives (Cluster E) acknowledged limits to economic growth, recognized the ecological crisis and expressed techno-skepticism. The other perspectives were in the middle of the spectrum. Based on the surveys, three audience segments were identified. Participants in Cluster 1 (41.1%) were the most optimistic towards technology and indefinite economic growth. Members of Cluster 2 (36.3%) did not express strong opinions. Participants in Cluster 3 (22.6%) acknowledged human unsustainability, expressed higher environmental concern and did not believe in indefinite growth. Sociodemographic factors (e.g. gender, political identification) correlated with the mental models and segments. Regarding the framing experiments, the messages influenced participant’s thoughts and emotions. Environmental messages invoked more references to resources and sustainability, while well-being messages generated more comments about overconsumption and happiness. Loss-framed messages caused greater negative emotions than gain-framed messages and the environmental message focused on losses generated the least hope and the greatest fear and anger among frames. There was no evidence that attitudinal responses were influenced by the frames. Most participants agreed with moving into an economic model with reduced consumption levels. This study provides data on topics that have been little explored and offers insights about the impacts of different post-growth messages.
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.
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 | 0.025 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".