Competitive Neutrality and the Challenge of Social Enterprise
Bibliographic record
Abstract
Globally, the past decade has seen many countries, including the United Kingdom, United States and Canada, introducing legislation that creates distinctive hybrid legal models for social enterprise. Although Australia has no dedicated legal model for social enterprise, its growing salience poses a challenge to competitive neutrality policy regimes. The challenge posed by social enterprise is both conceptual and practical. At the conceptual level, we argue that the underlying analytical framework of competitive neutrality sits uneasily with the premises of social enterprise. At the practical level, we show how the qualitative cost-benefit balancing flowing from the public interest test embedded in the Australian competitive neutrality regime is quite different from the way social enterprises achieve their social objectives, despite some apparent initial similarities. This challenge arises from the implicit baseline of competitive neutrality, which tends to generate analyses that place efficiency values in competition with social, environmental or other ‘non-economic’ values. Articulating and responding to this challenge is important for the enhancement of opportunities for social enterprise to grow and strengthen, and thereby contributes to rising political and consumer demand for more sustainable business models.
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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 | 0.025 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.075 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".