A Content Analysis of the Media Reporting on Canada 150 with a Special Focus on Coverage of Indigenous Issues in the Canadian Media
Bibliographic record
Abstract
In 2017, Canada celebrated a significant anniversary - 150 years since the enactment of the British North America Act, which granted Canada the status of Dominion. Celebrations were held across Canada to mark the occasion, with the main event that took place on July 1 at Parliament Hill. However, many Indigenous peoples, in light of past injustices and current problems, had no reason to celebrate and found the celebrations more like a reminder of colonialism. This is despite the government's effort to emphasize the theme of reconciliation with Indigenous peoples as part of the celebrations. This paper examines whether and, if so, how Indigenous perspectives on the celebrations were reflected in the Canadian media and whether these media contributed to the perpetuation of coloniality in Canada. At the beginning of the thesis, the current state of the academic debate on this topic, the terminology associated with Indigenous peoples, and the concept of coloniality are discussed. The thesis then examines the celebration of the sesquicentennial of Canada, with attention paid to both the organizational aspect and the relationship between the celebration and coloniality. The final section focuses on the media analysis, first introducing the methodology used and then presenting the results of the research....
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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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.018 | 0.042 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".