“I’ll Be Here:” Reflections on Representation and Research Communication Through Zine Work
Bibliographic record
Abstract
This article explores the decision-making process that culminated in the creation of a zine as a responsive research communication tool. The zine “I’ll Be Here” emerged from research conducted with community organizations in three Ontario cities as an alternative format to return research findings to participants in a form more accessible than a conventional academic manuscript. This reflective piece not only draws attention to the limitations of academic writing for knowledge mobilization, but also amplifies the need for research communication strategies capable of encapsulating the richness of knowledge producers’ experiences. Exploring the intricacies of communicating social science research effectively and contemplating the extension of responsive reciprocal research values into writing, this article emphasizes the potential of creative research communication methods like zine work to be effective, accessible, and inclusive avenues for knowledge mobilization.
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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 | 0.041 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.029 | 0.066 |
| Scholarly communication | 0.017 | 0.016 |
| Open science | 0.003 | 0.022 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 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".