Democratizing Public Consultation Processes: Some Critical Insights
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
Critical analysis of the Ontario government’s Lands for Life public consultation process uncovers the myriad ways in which the government put forward an economistic construct of Crown land, privileging industrial interests over all others. By reflecting on how this process went awry, future consultation processes might be further democratized, such that they would stand up to ethical scrutiny. This paper details several prescriptive suggestions and reflections as constructive input towards democratizing future land use planning processes. Specifically, it addresses a number of considerations that might be taken into account when posing the following questions: Who should consult the public? Who should be consulted? What should they be asked? And how should they be asked? Moving along the continuum towards greater inclusivity of marginalized social actors, representing a broader range interests, and mitigating power differentials ensures at the very least a more robust and deliberative democracy. This analysis challenges the entrenched government-industry collusion that has now become so prevalent, and explores how practices of ecological citizenship can be either promoted or constrained by the state.
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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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