Beyond innocence: the power of young people’s stories in resisting class-based inequality
Bibliographic record
Abstract
This study examines the FRONTLINE documentary Growing Up Poor in America, which sheds light on the stories of three young people from rural and suburban Ohio during the COVID-19 pandemic, emphasizing the harsh realities of class-based inequalities. Using a storytelling approach, this article aims to amplify the voices of these marginalized young people, challenging dominant developmental paradigms that often overlook their agency and understanding of systemic inequalities. The study explores how storytelling serves as a transformative tool to foster critical consciousness, inspire empathy, and encourage transformation. By prioritizing storytelling grounded in personal encounters, our approach not only confronts entrenched inequalities but also empowers marginalized young people by amplifying their narratives. We advocate for the transformative potential of storytelling to ignite meaningful dialogue, inspire action, and ultimately dismantle the barriers that perpetuate class-based disparities and other intersecting inequalities in the lives of young people.
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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 | 0.014 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.023 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".