Bibliographic record
Abstract
In this reflection, I tell the story of The Great Banana Fish Migration, a picture book I worked on throughout my time in the MES program, and I use it as a framing narrative to understand my return to Canada after being away for more than seven years. Having observed a sense of hopelessness pervading Canadian society upon my return, I explore the origins of this way of thinking and how it can act as an obstacle for positive social and environmental change. In my exploration I delve into how art can empower individuals to adopt alternative perspectives that creatively fuel awareness, resistance, and resilience. I also include examples from my ongoing artistic practice creating banana fish character art as examples of my findings on creativity. In an effort to embody the implications that art can have on culture, I recount the conception and creation of the project, Banana Fish in the City, where I create 100 ceramic banana fish figurines and place them around Toronto with a message of hope to disrupt the notions of hopelessness that inspired my research. Turning a critical eye to this project, I describe how my intentions may have been misaligned with the understandings of art and hope that my research uncovered. The execution of this project also allowed me to realize that the transformation I sought to catalyze in others was actually ongoing within myself and looking at the imagery in The Great Banana Fish Migration, I was able to understand my research on creativity, art, and hope from a deeply personal perspective that summarizes my own subconscious quest for hope, direction, love, and purpose throughout my time in the MES program. This reflection ultimately serves as a diary documenting my personal growth through the program, as a record of how the banana fish as both a concept and art object have grown in tandem with me, and as an example of the kind of thinking that I advocate for as a response to hopelessness in the face of societal and environmental crisis.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.015 | 0.008 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".