Bibliographic record
Abstract
Because This Land Is Who We Are is an exploration of environmental repossession, told through a collaborative case study approach, and engaging with Indigenous communities in Canada (Anishinaabe), Hawai'i (Kanaka Maoli) and Aotearoa (Maori). The co-authors are all Indigenous scholars, community leaders and activists who are actively engaged in the movements underway in these locations, and able to describe the unique and common strategies of repossession practices taking place in each community. This open access book celebrates Indigenous ways of knowing, relating to and honouring the land, and the authors' contributions emphasize the efforts taking place in their own Indigenous land. Through engagement with these varying cultural imperatives, the wider goal of Because This Land Is Who We Are is to broaden both theoretical and applied concepts of environmental repossession, and to empower any Indigenous community around the world which is struggling to assert its rights to land. The ebook editions of this book are available open access under a CC BY-NC-ND 4.0 licence on bloomsburycollections.com. Open access was funded by Knowledge Unlatched.
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 | 0.000 | 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) | 0.084 | 0.017 |
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; both teacher heads agree on what is shown here.
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".