Nationalisms and identities among indigenous peoples : case studies from North America
Bibliographic record
Abstract
Contents: Martina Neuburger/H. Peter Dorrenbacher: Introduction: Nationalisms and Identities among Indigenous Peoples - John George Hansen: Decolonizing Indigenous Histories and Justice - Linda Sue Warner/Keith Grint: War and Peace: Issues of Leadership in American Indian Communities - Sandra Busatta: The Akwesasne Mohawk at the Margin of the State - Miranda C. Laber: 'Planting the Seeds of Change': Indigenous Education, Nation-Building and Democracy in the United States - Herman Michell: Transcending the Winter Time: The Legacy of Residential Schools and the Role of Indigenous Places of Higher Learning in an Era of Reconciliation - Punyashree Panda: To Be or Not To Be Native: Residential School, Official Status and Metis Women in Maria Campbell's Halfbreed and Beatrice Culleton's In Search of April Raintree - Kevin A. Johnson/Joseph W. Anderson: The Native American Hip-Hop Nation: A Nationalist Movement for Sovereignty - Brian de Ruiter: The Empire Films Back: Constructing Identity and Resistance Through the Selective Films of Chris Eyre - Monika Ludescher: The Rights of Indigenous Peoples in Latin America from International and Comparative Perspectives - Christina Goschenhofer/Katrin Singer: Mexican Indigeneities in Motion, Mexican Identities in Negotiation - Anne C. Uhlig: The Notion of the Nation Compared: Deafhood and Indianness.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.025 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".