Bibliographic record
Abstract
In this dissertation, I embraced bricolage (Denzin & Lincoln, 2000, 2018; Kincheloe, 2001, 2005b; Kincheloe, McLaren, & Steinberg, 2011; Rogers, 2012; Steinberg, 2006; Steinberg, Berry, & Kincheloe, 2020) as a responsive, dynamic, and reflexive research orientation. Guided by Jo-ann Archibald’s (2008a, 2008b) storywork principles, I conducted ethnographic interviews and gathered the stories of youth who graduated the year of the 2013 High River flood. I wondered how they experienced the flood and post-disaster recovery, as they transitioned from life-in-schools to life-out-of-schools. Conducting research with a vulnerable population required an ethic of care (Gilligan, 1982; Noddings, 1984, 2012). Through storywork, I was conscious of my responsibilities to the participants and their stories. I engaged in deep listening and critical reflection to learn from the youths’ experiences. Following the four directions teachings of Elder Bob Cardinal of the Maskekosihk Enoch Cree Nation, I considered the emotional, spiritual, mental, and physical well-being of the youth, as evidenced in their stories. Using Elder Cardinal’s holistic framework as a guide (Elder Bob Cardinal, personal communication, September, 2016 to July, 2017; Latremouille, 2016; University of Alberta, 2016), I created and re-created a holistic conceptual framework in response to the emergent needs and ideas shared by the youth. I re-presented their narratives in storied métissage, entered into generative dialogues with the holistic teachers, and engaged in meaning-making processes. Moving from listener/researcher to storyteller, I am responsible for carrying the stories of the youth forward to new audiences towards transformational learning and holistic well-being.
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".