Is My Colonialism Showing? A Reflexive Case Study.
Bibliographic record
Abstract
About a decade ago, I was told by a family member that our ancestor, who we all believed to have been a French-Canadian fur trader, was of the Wolastoqiyik / Maliseet Indigenous People. This was shocking considering my white upper middle class, Dutch/Irish, conservative background. Through my time at Grand Valley State University (GVSU), I was able to meet Lin Bardwell, Native American Student Initiative Coordinator and Assistant Director of Multicultural Affairs. Through her, I have been given the opportunity to be mentored in the ways of the Anishinaabeg People of West Michigan. My experiences have stirred an even deeper desire to see more equitable systems in place for my kin and other marginalized groups. That is why this reflexive case study will ask the following question: How have colonial research methodologies on North American Indigenous Peoples and Indigenous Knowledge Systems impacted the interrelationships between Indigenous culture, community, business, and philanthropy? My project is Participatory Action Research (PAR)-informed, utilizing a Strengths Enhancing Evaluation Research (SEER) approach through the process of story-gathering, while also examining anthropological resources through a Decolonizing / postcolonial methodology within a reflexive case study. Lastly, I will integrate the Seven Grandfather Teachings of the Anishinaabeg people into the framework of my project. “The Seven Grandfather Teachings are the principles of character that each Anishinaabe should live by. Love, Respect, Bravery, Truth, Honesty, Humility & Wisdom” (American Indian Health Service of Chicago, 2021). Embracing the SEER approach within a Reflexive Case Study will allow me to continually assess and adjust my own personal biases, while also learning and growing from the wisdom of Indigenous Culture and Knowledge Systems, including the Seven Grandfather teachings.
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 | 0.000 | 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 | 0.000 | 0.000 |
| 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".