Mapping civil society: the ecology of actors in the Toronto region greenbelt
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
Civil society’s potential as a force for solving complex societal problems – particularly those that require a challenge to the status quo – has provoked practical and theoretical interest, with its potential largely reliant on the perception that it is a ready if variable source of social capital resources. However, there are no guarantees that civil society will use its social capital for the greater good. Civil society encompasses a range of groups, some more inward-looking and oriented to private interests, and others more outward-looking and oriented to public interests. This divergent character of civil society was evident in the three campaigns for greenspace protection that eventually led to the creation of the Toronto region greenbelt, where civil society organisations (CSOs) from both growth and conservation camps contended for influence, each succeeding at different times. But over time (a time when state actors were increasingly in need of non-state partners to help solve complex governance problems), coalitions of environmental CSOs in the three campaigns – to protect the Niagara Escarpment, Oak Ridges Moraine and surrounding countryside – became more effective at influencing government to protect greenspace. A comparison of the coalitions using a framework based on key attributes of CSOs – missions and memberships – suggests that the environmental coalitions were more effective when they recruited more members with a diverse set of resources arising from both bonding and bridging social capital. In general, the more inclusive and public-interested the CSOs, the more effective the challenge to the status quo.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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