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Navigating Dreams and Realities: An Intersectionality Approach to Understand Rural Youth Aspirations in Colombia

2025· article· en· W4408764403 on OpenAlexaffvenue
Margarita Fontecha

Bibliographic record

VenueRural Review Ontario Rural Planning Development and Policy · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEducation in Rural Contexts
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsIntersectionalitySociologyGender studies

Abstract

fetched live from OpenAlex

Rural youth studies identify that rural youth aspirations and life courses are dynamic and change over time. They are the outcome of the relationship between the context and the agency. However, few studies have explored how different social characteristics (e.g., age, sex) might influence the development of aspirations and how these characteristics and the relationship with the context where violence is a cross-cutting variable could exacerbate power imbalances. In regions where licit and illicit economies coexist, the exercise of agency by rural youth becomes an act of rebellion. This study employs an “I will be” method, grounded in Possible Selves theory, agency, and intersectionality, to explore rural youth's aspirations and life trajectories in La India, Colombia, from their own perspective. Findings reveal a significant tension between the aspirations of young men and women and the perceived attainability of their goals. In these communities, youth participation is limited, with their voices marginalized by social norms shaped by violence and historical conflict. This is particularly pronounced for young women, those without social support networks, and young adults living independently. Understanding the factors influencing rural youth decision-making is essential for developing context-appropriate policies and programs that can support their aspirations and provide pathways to meaningful change.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0070.008
Scholarly communication0.0090.007
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.088
GPT teacher head0.402
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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