Us/Them, Me/You: Who? (Re)Thinking the Binary of First Nations and Non-First Nations
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
Names speak who we are and who we do not wish to be. Issues of belonging, entitlement, representation, and autonomy related to the naming represented in the socially constructed binary—First Nations and non-First Nations—are briefly examined. A legacy of colonialism is the dichotomy of us/them, characterized with a variety of terms. These include, among others, Native, Status Indian, Amerindian, Aboriginal, First Nations, Canadians, Euro-Canadians, Anglo-Canadian, and White. Just when is it appropriate to use the terms? The terms exclude individuals of mixed political, cultural, or other heritages, or recent immigrant Brothers and Sisters. Although the binary is necessary to explain longstanding geopolitical, spiritual, economic, and other injustices, the dualism obscures nuanced understandings of interrelated issues of class, gender or other discrimination. Unthinking use of the terms of this dichotomy contradicts some traditional teachings, which state that all humans are members of the same human family. (Over)Reliance on this dichotomy may enable forgetfulness about other binaries to consider.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.098 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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