The Commodification of the Female Body on Instagram: A Systemic Review and Meta-Analysis
Bibliographic record
Abstract
Instagram is an application that is used by both the public and numerous corporations to strategically impact the mental wellbeing of many young females for capitalist gain. In Canada’s modern capitalist culture, large corporations like Instagram use market interests to guide what users see and impact the products of which their audience can access. This small meta-analysis aims to determine how Instagram usage can fundamentally impact female youth on a global scale. These articles were gathered from a global review of the literature and included influential articles from Canada, Spain, and Australia. This research has shown that the commodification, or process of turning young females’ bodies into commodities, significantly negatively impacts their wellbeing. Furthermore, it was discovered that social media algorithms, Instagram’s Terms of Use, and the application’s accessibility of its users all impact how females build a sense of identity today.
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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 | 0.009 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".