A framework proposal for assessing social impacts in subnational circular economy experiments
Bibliographic record
Abstract
As awareness of the sustainability challenges facing global economies grows, many countries are adopting circular economy (CE) policies that prioritize resource reuse, waste reduction, and sustainable production and consumption strategies. Subnational governments are also advancing these efforts by developing CE roadmaps to support the growing momentum of initiatives led by businesses and other stakeholders. However, these policies can lead to unintended social impacts, both positive and negative. In this study, we explore 11 social externality hypotheses identified through a literature review and a case study of Montreal's recent CE roadmap adoption. Preliminary findings suggest that while CE initiatives are known for promoting job creation and strengthening networks, their wider social impacts on well-being, inclusion, finance, culture, education, and justice are often overlooked, with potentially negative consequences underrecognized. This highlights the need for a systematic approach to identify and manage social externalities, helping policymakers enhance the benefits and mitigate the risks associated with CE transitions at the subnational level.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".