“I Used to Love Scheifele:” Dominant Narratives on Reddit About the Canadian Division of the Stanley Cup Playoffs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The community-moderated content aggregation social media site Reddit has emerged as a popular destination for discussion of topics of interest in news, sport, and entertainment. This study explored the discourse of hockey fans during the playoff rounds of the Canadian Division in the 2021 Stanley Cup playoffs. The study analyzed fan discourse around two incidents which garnered significant media attention, and subsequent Reddit chatter—the inadvertent knee-on-head collision that knocked Toronto Maple Leafs’ captain John Tavares out of Round 1 and the deliberate late hit by Mark Scheifele of the Winnipeg Jets, leading to his suspension for the remainder of Round 2. On Reddit, both incidents revealed a community of hockey fans eager to engage in spirited, sometimes profane, discussion. Very quickly, discussion of the incidents led to the creation of a dominant narrative on Reddit, with the architecture of the site itself helping to inhibit alternative points of view. This contradicts the popular view of Reddit as a fan-powered community because of affordances which inhibit dissent and reward repeating other debate participants. This instant in-group creation could ultimately act as a barrier to fandom among Reddit’s 850 million users not as passionate about particular narratives of hockey.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it