Commemoration, Veneration, and Inspiration: Constituting the Terry Fox Public
Bibliographic record
Abstract
There are few figures in Canada as widely known and loved and remembered as Terry Fox. This article highlights how this contemporary sensibility has been constituted by examining the rhetorical “stickiness” of Terry Fox in public memory as spearheaded by the Terry Fox Foundation. I consciously avoid analysis of Terry Fox monuments and the enfranchisement of Terry Fox within museums. Rather than interrogate these material sites associated with Terry Fox, I seek to understand how more intangible Terry Fox commemoration and ritualized acts operate within popular and public culture as affective practices, mediating forms of national and post-national civic identity. My focus is on Terry Fox Runs and the promotional culture and texts surrounding them. I approach these cultural forms and practices through a lens of rhetorical criticism. The public memory of Terry Fox acts as a medium of connection with a certain time and place but, crucially, does not create an affective bond to the past as much as encourage an attachment with fellow Terry Foxers, civically, somatically, emotionally, and symbolically imbuing individuals with a feeling of purpose by being inspired by Terry Fox’s actions in the past.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.026 | 0.038 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".