Mainstream Media Portrayal of Banishment and Nation-Imposed Punishment
Bibliographic record
Abstract
“In a traditional village, we wouldn’t have a teepee with no door on it and throw somebody in there. We wouldn’t cast them out, because banishment meant death. What we had to do was restore relationships” – Ryan Beardy (Thorpe, 2022).\nThe following project examines the representation of Indigenous traditions, customs, and issues in Canadian mainstream media. Specifically, this project is interested in the portrayal of banishment as an Indigenous practice in Canadian mainstream news outlets. This project is based on an interpretive paradigm informed by grounded theory and concepts of media framing, postcolonialism, settler colonialism and restorative justice. Nineteen Canadian mainstream media articles discussing banishment were selected through the database Factiva which were then coded and analysed. The results of this analysis showed four key themes that will contribute to the current literature on Indigenous issues portrayal in settler-colonial mainstream media: (1) an ideological distinction between western settler and Indigenous conceptions of banishment; (2) erasure of Indigenous ways of knowing from media coverage of Indigenous practices; (3) the challenges of using banishment as punishment or crime prevention in a modern, industrialised landscape; and (4) how the Canadian state has leveraged media to promote the myth of Indigenous self- governance and what I call the Façade of Indigenous Agency (FIA). The FIA is, what I argue to be, a propaganda technique employed by the Canadian state to smooth over tensions between settler-Canadians and Indigenous peoples living in Canada as well as between the state itself and Indigenous peoples.\nThis work contributes to the decolonization of media and literature by shedding light on how colonizing narratives operate through mainstream media. As expanded on in this project, the current literary landscape and historic account of Canada’s past is deeply entrenched with colonization and imperial thought. As such, it is important to examine the ways in which these detrimental ideologies are exist and are reinforced through mainstream media. Therefore, the decolonization of the media and discussions of media’s strengthening of western values is imperative as failing to do so will further silence Indigenous voices and stories. If Canada’s goal of decolonization and reconciliation is true, the state should be quite concerned with the portrayal of Indigenous culture as well as the Façade of Indigenous Agency.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".