SOCIAL IDENTITIES, RISKY BEHAVIORS, AND THE RURAL YOUTH EXPERIENCE
Bibliographic record
Abstract
Throughout the global north, rural youth are often marginalized within landscapes and in academic literature. Prior research on rural youth often focuses on health access and educational attainment, but topics of rural teenage socio-spatial negotiations, place making tactics, and social groupings remain unexplored. In an attempt to fill this gap, this study examines rural teens in Northern Vermont and inspects how and where these young people create social spaces. The analysis emphasizes participants’ perspectives, beliefs, and experiences in this analysis. Findings suggest that each young person experiences rurality differently. Factors such as a young person’s social identity, class, race, gender, and more can impact their well-being and shape the way they view their community and the greater world. This study found that small, tight-knit rural communities can create an amplified class structure, meaning young peoples’ identity, reputation, and social group is closely tied to their family’s income level. Further, other factors such as varying policing methods, access to the Canadian border, seasonal changes, and the COVID-19 pandemic have merged to create unique social and cultural circumstances that young Northern Vermonters must grapple with. At its core, this research shows that young people in the area lack designated social spaces and need targeted community planning to create more accessible spaces that better meet the needs of all young people. Further research is needed to provide a more robust understanding of rural communities, as each place is unique and has specific needs.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".