Media Images: Influence on Concepts of Race and Beauty
Bibliographic record
Abstract
“Media Images: Influence on Concepts of Race and Beauty,” is a photographic essay which was motivated by my own personal struggles with concepts of beauty and race as a woman of colour growing up in Canada surrounded by media images of white beauty. In my project, I propose that the media institutionalizes a distorted perception of beauty, which reflect imperialist white supremacist capitalist patriarchal ideologies. Representation across multiple groups of gender, race, ability, age, class, etc. is excluded in the media. The lack of diversity in the media has a significant effect on women and girls who do not fit the narrow portrayals of the white, thin, blue-eyed beauty archetype. These women learn that the essentialist, biological elements of their identity are neither desirable nor worthy. The exclusion of women and girls across a wide range of groups legitimizes the dominance and normalization of white power and privilege, as the only representation of beauty that is seen in the media is one constructed by the white gaze. The deeply embedded ideologies within media images affect our consciousness, ideas, and perceptions of beauty and race. Along with my essay, I used photographs to illustrate the struggle that women of colour face with concepts of race and beauty, as a result of media images. Through these photographs, I wanted to portray the gaze from different perspectives – the white supremacist, imperialistic, capitalist, patriarchal gaze that society holds as well as the internal gaze that women of colour personally hold of themselves. I wanted to include photographs to demonstrate the strength that images possess in portraying messages. The message that I seek to portray through my photographic essay is that a more diverse representation of women in the media is crucial in order to challenge the imperialist white supremacist capitalist patriarchal ideologies and make progress towards a healthier environment for girls and women of colour, among other marginalized groups. The photo-essay can be viewed at: http://leneeson.com/2014/03/19/media-images-girls-and-identity/
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.
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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.012 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".