Scaling sustainability in businesses with a post-growth orientation: An exploratory empirical study
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
To avoid negative social and ecological consequences associated with growth-based economics, businesses with a post-growth orientation intentionally forgo scaling for profit maximization and instead seek to scale positive socio-ecological impacts. This study investigates 35 small and medium-sized businesses (33 private and 2 cooperatives) with a post-growth orientation to examine how they strive to scale their positive socio-ecological impact. Our findings reveal four distinct scaling approaches: Enhancement, Expansion, Bridging, and Collaboration. We provide a typology of these four approaches and explain how they can be interlinked to create synergy. Our study shows how private businesses can participate in creating a post-growth economy, thus broadening the scope of previous post-growth research that has focused on other organizational forms such as social enterprises, benefit corporations, and cooperatives.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it