Chasing colonization back: rethinking parks, returning place-names, and restoring buffalo medicine—an interview with Ninna Piiksii, Dr. Mike Bruised Head
Bibliographic record
Abstract
In this interview, we hear from influential Blackfoot Elder and Cultural Educator Ninna Piiksii, Dr. Michael Bruised Head. Mike reflects on the colonial naming of national parks and the need to return to Indigenous place-names, examining how we occupy a pivotal moment where park staff are more open to substantive Indigenous engagement and presence within parks, although more needs to be done. Drawing connections across topics that may initially seem discrete, Mike reflects on his experience as a survivor of the Canadian residential school system, colonial dispossession by parks and more broadly, and how Blackfoot restoration efforts—including the return of buffalo or iinnii —can offer paths for healing from these traumas and build a more just, Blackfoot-led future. Through this, Mike asks us to rethink the profound value and potential of conservation, pushing beyond Western understandings. He closes by asking the interviewers to reflect on what motivates them to support Tribal buffalo restoration, turning the tables on the interviewer and interviewee, and reinforcing the importance of connection and responsibility among non-Tribal research collaborators. We open with an introduction to Mike and then turn to hear his words. The interview format reflects a growing trend of expert-interviews-as-articles and Indigenous practices of oral knowledge transmission. We also link to an audio recording of the interview to allow readers to become listeners and hear Mike’s words in full context. The conversation and format are offered in the spirit of opening more space for Indigenous—and particularly Blackfoot—voices, perspectives, and methodologies in conservation scholarship.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".