Bibliographic record
Abstract
This paper examines the ways in which colonial ideologies influenced the presentation of Native Hawaiians in American media throughout the nineteenth and twentieth centuries. Since the acquisition of the Hawaiian Islands as a U.S. territory in 1898, American cartoonists, advertisers, authors, filmmakers, and others have promoted racist, sexist, and oversexualized versions of Native Hawaiians to the American public because of their deeply ingrained, sometimes unconscious, colonial ways of thinking. Although Indigenous Studies is a growing area of interest in the academy, research on Native Hawaiian media representation and the impact of stereotypes on both Native Hawaiian identity and public views of Native Hawaiians is scarce. This paper uses political cartoons, travel ephemera, film footage, and various forms of print media to bring to light the most prominent stereotypes of Native Hawaiians and explore how the origins of these stereotypes can be traced back to American colonialism. Unlike pre-existing works, this paper scrutinizes various examples of Native Hawaiian media representations from an intersectional perspective, considering racial-, gender-, and sexuality-based approaches. It also critically examines the role of exoticization, instead of focusing on only one of the aforementioned approaches. By outlining the fallacious stereotypes of the Native Hawaiian community and explaining their origins, this paper can help arm the media industry with the necessary tools to create more culturally competent media content.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 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".