An examination of the integration processes of Anishinaabe smudging ceremonies in Northeastern Ontario health care facililties.
Bibliographic record
Abstract
In part of the Anishinaabek storytelling traditions, ceremonies emerged from the teachings from the simple act of offering tobacco to more complex ceremonies such as the rain dance. The smudging ceremony is no different because it has its own creation story that emerged with the four medicines (Benton-Banai, 1988; Geniusz, 2009). This research aims to contribute to the an understanding of how the Indigenous smudging ceremony takes place and how it is made available to individuals who want to practice this form of ceremony in urban health care settings. There has been limited research conducted on Indigenous ceremonies and even less on the smudging ceremony, which highlights the literature gap on scholarly souces on these traditional ways of healing written by Indigenous People. Most of the information on the smudging ceremony is from online sources, Elders that are not published, and non-Indigenous people. Although there are many books, how-to manuals, and kits that provide medicines that teach interested individuals on the smudging ceremony, these could be found in the New Age healing sections at bookstores or in alternative healing shops that many would not find to be a credible academic source. None of these sources address why the smudging ceremony is crucial and how it has been suppressed as part of a much larger process of cultural genocide. This research is situated within an historical context to better understand why the ceremony has not been accessible within these health care facilities. There are three facilities examined in Sudbury and Parry Sound, Ontario. The facilities and policies are compared to understand the integration processes as well as ensuring that the smudging ceremony is more accessible. In addition, the contribution of this thesis is to have the smudging ceremony accessible and accommodated outside the walls of medicine/healing lodge rooms. Lastly, this study is examined through the Anishinaabe perspective that complements the decolonization approach as it recommends meaningful pathways that support the efforts of reconciliation.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.016 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".