The discursive articulation of Canadian identity through Don Cherry’s Coach’s Corner
Bibliographic record
Abstract
Have you ever thought about how you would define your identity? How about delineating your nation’s identity? Attempts at providing a fully-fledged definition of Canadian identity have been going on for several decades. Still, the debates about a unified description of Canadianness remain unresolved. Nowadays, the media provide one of the platforms offering an interesting insight into the process of identity negotiation and present an important means of facilitating identity construction. The present study inspects the discursive construction of national identity within Canadian context. Specifically, the study focuses on Coach’s Corner, currently the longest running television program in Canada, and its main personality – Don Cherry. The data for the analysis has been collected throughout the National Hockey League 2015/2016 regular season when Coach’s Corner airs weekly on Saturday night. Relying predominantly on Critical Discourse Analysis and its sub-disciplines, the study explores discursive strategies and linguistic devices employed in order to articulate Canadian national uniqueness on the one hand, and how to position Canadian collectivity towards other nations on the other hand. Also, the study explores the presentation of the in-group members and the out-group members on the show and how the discourse is appropriated in order to create an inclusive framework for the members of the former. By subjecting the collected data to qualitative research, the present study aims to demonstrate that there exists conceptual polarization between the inner and outer group members that is created by adopting contrasting discourses by Don Cherry. Furthermore, the study argues that Cherry negotiates Canadian identity by foregrounding the positive qualities of the in-group and the negative qualities of the out-group.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".