Bibliographic record
Abstract
Post-Colonial Optimism: The news is not good.The news is good.I find it difficult to make sense of the activities that are all around us.We watch and listen to the apology for the residential schools, the second apology in a decade; We read reports on the lack of potable water in First Nations communities across the country; We listen to the music of the JUNO Aboriginal music award winners; We listen to our national leaders lambast the government for their inaction on economic development, training, education, treaty rights, self government and health; We access traditional healers through Aboriginal-controlled health care centres; We use Indigenous Knowledge in our everyday work lives alongside the knowledge we gained in colleges and universities.We watch as Aboriginal peoples move into urban centres looking for better lives; as others move to reserve communities to escape from urban poverty and violence.Indians become Aboriginal and First Nations and Indigenous and Métis and Inuit.Cree become Neyaw; MicMac become Mik'maq; Eskimo become Inuit; Blackfoot become Siksika; Ojibway become Anishnaabe (or Anishnabeq or Anishnawbe).Study after study documents the difficult living conditions that many of our brothers and sisters face: racism and prejudice, low incomes, poor education that doesn't provide the skills necessary to work in a rapidly changing economy, poor physical and mental health, poor housing, to list just a few of the many indicators that measure and report on our lives.When examined over a lengthy
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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.157 | 0.042 |
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".