Teacher candidates in the urban Canadian classroom: Rereading the digital citizenship paradigm through atom Egoyan’s Adoration
Bibliographic record
Abstract
In this paper, inspired by the challenge Atom Egoyan provides for educators in Adoration, I offer the film as a heuristic to digital citizenship to read two university driven digital initiatives. I argue that digital citizenship is always emerging, and can be understood as a form of currere, where the personal and historical underpin “digital acts” that rewrite the notion of subjectivities as being disembodied in the seemingly atemporal space of being online. As a teacher educator who is part of the Urban Communities Cohort (UCC) team, one of the five different streams incoming Bachelor of Education students choose upon entering the program at the University of Ottawa, I am interested in exploring the concept of currere as it applies to digital citizenship and asking why it matters to urban schools in Ottawa. My inquiry is part of a larger project entitled, Developing Mobile Media Spaces for Civic Engagement in Urban Priority Schools, located in Ottawa, Canada that is supported by Social Sciences and Research Council of Canada (SSHRC) Insight Grant.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.042 | 0.037 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".