Bibliographic record
Abstract
A World You Do Not Know explores the wilful ignorance demonstrated by North America’s settlers in establishing their societies on lands already occupied by indigenous nations. Using the Innu of Labrador-Quebec as one powerful contemporary example, Colin Samson shows how the processes of displacement and assimilation today resemble those of the 19th century as the state and corporations scramble for Innu lands. While nation building, capitalism and industrialisation are shown to have undermined indigenous peoples’ wellbeing, the values that guide societies like the Innu are very much alive. The book ends by showcasing how ideas and land-based activities of indigenous groups in Canada and the US are being maintained and recast as ways to address the attack on cultural diversity and move forward to more positive futures.; This is a thoughtful book, highlighting the arrogance with which we approach indigenous ways of knowing and being, while also highlighting the continued resistance of indigenous peoples to western colonisation. -David MacDonald, Professor of Political Science, University of Guelph ; A World You Do Not Know explores the wilful ignorance demonstrated by NorthAmerica’s settlers in establishing their societies on lands already occupied by indigenous nations. Using the Innu of Labrador-Quebec as one powerful contemporary example, Colin Samson shows how the processes of displacement and assimilation today resemble those of the 19th century as the state and corporations scramble for Innu lands. While nation building, capitalism and industrialisation are shown to have undermined indigenous peoples’ wellbeing, the values that guide societies like the Innu are very much alive. The book ends by showcasing how ideas and land-based activities of indigenous groups in Canada and the US are being maintained and recast as ways to address the attack on cultural diversity and move forward to more positive futures.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.046 | 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 itClassification
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".