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Record W4397007906 · doi:10.3389/fhumd.2024.1352329

Chasing colonization back: rethinking parks, returning place-names, and restoring buffalo medicine—an interview with Ninna Piiksii, Dr. Mike Bruised Head

2024· article· en· W4397007906 on OpenAlexaffabout
Elizabeth Lunstrum, Madison Stevens

Bibliographic record

VenueFrontiers in Human Dynamics · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsUniversity of Lethbridge
FundersNational Science Foundation
KeywordsIndigenousContext (archaeology)InterviewSociologyConversationColonialismMedia studiesValue (mathematics)HistoryPsychologyAnthropologyCommunicationArchaeology

Abstract

fetched live from OpenAlex

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.876
Threshold uncertainty score0.246

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0330.019
Scholarly communication0.0060.008
Open science0.0020.007
Research integrity0.0040.015
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.075
GPT teacher head0.269
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2024
Admission routes2
Has abstractyes

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