Indigenous and decolonial futures: Indigenous Protected and Conserved Areas as potential pathways of reconciliation
Bibliographic record
Abstract
Crown governments, the conservation sector, academics, and some Indigenous governments, communities, and organizations are framing Indigenous Protected and Conserved Areas (IPCAs)—a newly recognized form of Indigenous-led conservation in Canada—as advancing reconciliation with Indigenous Peoples. Yet it is often unclear what is being, or could be, reconciled through IPCAs. While highly diverse, IPCAs are advanced by Indigenous Nations, governments, and communities who protect them, with or without partners, according to their Indigenous knowledge, legal, and governance systems. IPCAs may be expressions of “generative refusal,” visions of Indigenous futures, and commitments to uphold responsibilities to the lands, waters, and past and future generations. IPCAs refuse settler colonial ontologies including the expectation of ongoing white settler privilege, which relies on the continued appropriation of lands and resources. By examining the practical, relational, and systemic challenges Indigenous Nations advancing IPCAs encounter, we discuss opportunities for Crown governments and the conservation sector to cultivate decolonial responses. Indigenous Nations advancing IPCAs may face challenges with resource extraction, laws and legislation, financing, relationships and capacity, and jurisdiction and governance. We contend that IPCAs could be pathways of reconciliation if Crown governments and the conservation sector support IPCAs in ways consistent with the recommendations of Indigenous leaders. This requires dismantling the roadblocks arising from settler ontologies and institutions that impede IPCA establishment and ongoing stewardship. Thus, not only could Indigenous futures be advanced, we might also cultivate decolonial futures in which all peoples and species can thrive.
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.
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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.027 | 0.082 |
| Scholarly communication | 0.020 | 0.024 |
| Open science | 0.003 | 0.023 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 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".