Transmedia Storytelling Responses by Canadian Male Teachers in an Era of Truth and Reconciliation: A Narrative Analysis
Bibliographic record
Abstract
Among the 2015 Truth and Reconciliation Commission of Canada’s 94 Calls to Action, are four that focus specifically on Education for reconciliation, and one in particular, 62ii, reads, “Provide the necessary funding to post-secondary institutions to educate teachers on how to integrate Indigenous knowledge and teaching methods into classrooms”. As a humble attempt at a creative and meaningful response to these recommendations and challenges, my transmedia storytelling study invited four willing and interested non-Indigenous Canadian male teachers to read and reflect on a curated list of Indigenous authors and scholars, to create their own chosen and unique transmedia storytelling response to the experience, such as a painting, a series of photographs, a sculpture, or an essay, and then to share their experience by participating in a Story Circle. The Story Circle method (Parks, 2023), also known as a talking circle or sharing circle (Rieth, 2023), allows participants to come together to share stories about a particular topic, event, or experience. Throughout the study, I leaned heavily on Jenkins’ (2006) definition of transmedia storytelling, “A transmedia story unfolds across multiple media platforms, with each new text making a distinctive and valuable contribution to the whole…”, but I also wanted to expand the definition for use in educational settings, and in this case, to introduce creative possibilities for teachers seeking to integrate Indigenous ways of knowing into their curricula. My goal in this study was to challenge my participants to “begin to deconstruct their colonial perspective” by inquiring narratively through transmedia storytelling. For my methodology, I chose narrative analysis (Polkinghorne, 1995), a sub-category of narrative inquiry (Clandinin, 2006), because I also wanted to investigate my own “lived experience” as a non-Indigenous Canadian male teacher attempting to integrate Indigenous knowledge into my instructional planning and teaching best practices. The one recurring question that continued to surface throughout the study, and that emerged again towards the end was, “What contribution or contributions will this research make in the slow journey towards truth and reconciliation?” Here are 4 hopes that I have: (1) Hope One. That Transmedia storytelling research approaches offer creative and impactful opportunities for post-secondary instructors to authentically and meaningfully integrate Indigenous authors and scholars, and in some cases where applicable and appropriate, Indigenous artists and musicians into their curriculum, whether the curriculum is arts-focused or not. (2) Hope Two. That Transmedia storytelling research approaches allow students to explore and creatively respond to stories and learnings about residential school survivors, Canada’s residential school system, and First Nations, Metis, and Inuit language and culture, alongside broader and deeper topics around truth and reconciliation. (3) Hope Three. That Transmedia storytelling research approaches be offered not just to post-secondary instructors and students, but also to students, staff, administrators, parent groups, and school boards in a Kindergarten to Grade 12 public education setting. (4) Hope Four. That Transmedia storytelling research approaches also be considered as a creative strategy beyond topics of truth and reconciliation to further support academic, social, and psychological learning alongside more traditional teaching and learning approaches in both public and post-secondary settings.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.044 | 0.021 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".