Decolonizing climate crisis and housing infrastructure: learning from Indigenous land-based perspectives
Classification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".
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
In the face of the escalating climate crisis, coupled with the ongoing challenges in housing infrastructure, this research undertakes a transformative journey toward decolonization by centering on Indigenous land-based perspectives. As Indigenous and racialized scholars, we critically examine the intersection of the climate crisis and Indigenous housing infrastructure from Indigenous land-based perspectives. Following the decolonial reflective research framework, this research commences by critically examining the historical legacy of colonization on Indigenous communities, acknowledging that mainstream climate and housing policies often perpetuate systemic injustices. This study aims to deconstruct prevailing paradigms that have marginalized Indigenous voices and perspectives in climate and housing discourse. Moreover, the research illuminates the innovative approaches and practices that Indigenous peoples employ to mitigate the impacts of the climate crisis on their homes and communities. It serves as a repository of valuable insights for policymakers, scholars, and practitioners, offering a blueprint for fostering resilience that aligns with Indigenous values. This research aspires to contribute to the broader discourse on climate justice and equitable housing by advocating for a paradigm shift that recognizes and respects the traditional knowledge embedded in Indigenous land-based perspectives. Through this decolonizing lens, the study undertakings to carve a path toward more inclusive, sustainable, and culturally sensitive solutions in the critical intersection of the climate crisis and Indigenous housing infrastructure.
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 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 | 0.001 |
| Science and technology studies | 0.014 | 0.001 |
| 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