Bibliographic record
Abstract
This article describes an Indigenist re-search project where I gathered stories from my mother who went to the St. Johns Anglican Residential School. The re-search project was a personal, close to home project that took place from 2015 to 2017. This article articulates a personal, layered, wholistic and seasonally governed Indigenist methodology. It illustrates what makes a project Indigenist by way of its focus and process that is wholistic and guided by an Anishinaabe worldview calling attention to spirit, heart, mind and body. In this article, the term re-search versus research is applied to indicate an act of ‘looking again’ at how to re-search. My hyphenated re-search restores Indigeneity and Indigenous knowledge in how one comes to know (knowledge production). This article demonstrates a reworking of how I engage in research through an act of re-searching through memory and story sharing. The methodology presented herein illustrates a process of gathering stories, having conversations, making meaning of those stories, and reframing and representing them in multiple modes such as film, creative arts and text. My Indigeneity as well as my Anishinaabe teachings and knowledge are the foundation of how I searched and guided this wholistic process. Pivotal to this project is the relationship of daughter and mother and the restoring of both knowledge and relationship through re-search. This article articulates a methodology that is steeped in relational accountability, seasonally guided and restoring of Indigenous knowledge.
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 | 0.019 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.024 | 0.035 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.004 | 0.022 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".