Integrating Justice and Equity into the Regional Conservation Planning Process
Bibliographic record
Abstract
Ecological conservation and restoration efforts in urban landscapes necessarily interact with environmental justice issues, and conservation practitioners are challenged to incorporate these important dynamics into their process. This presentation focuses on a case study of a recent effort, led by the Regional Habitat Connectivity Working Group of the Portland/Vancouver area, to meaningfully integrate the principles of Justice, Equity, Diversity and Inclusion into their Strategic Action Plan (SAP). The Working Group and consultant team completed a full audit of the draft SAP and facilitated multiple internal engagement sessions which resulted in; recommended changes to the plan, a draft community engagement framework and a geospatial dataset, based on community vulnerability factors, to help focus relationship building and engagement efforts. The highest-level message of this work is that the movement to respond to the biodiversity and climate crises is inextricably connected with movements to expand civil rights, reduce income inequality, and achieve social justice. White supremacy and the unsustainable exploitation of natural resources are two sides of the same coin, and it is becoming increasingly clear that there is no addressing one of these problems without addressing the other. 215 years of settler colonialism and systemic racism have been inscribed upon the region’s landscape itself, directing the distribution of environmental amenities and burdens across our communities, and delineating barriers and corridors affecting the movement of plants and animals. At the same time, the momentum that is building in these movements separately gains orders of magnitude more efficacy and meaning when pursued together.
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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 | 0.067 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.020 | 0.028 |
| Scholarly communication | 0.025 | 0.014 |
| Open science | 0.003 | 0.021 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".