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Record W4407909874 · doi:10.1080/03054985.2025.2468207

Bridging the gap: educational aspirations and expectations in Latin American intermediate territories

2025· article· en· W4407909874 on OpenAlexfundno aff
Thibaut Plassot, Isidro Soloaga, Chiara Cazzuffi, C. Leyton

Bibliographic record

VenueOxford Review of Education · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsnot available
FundersMinistry of EconomyUniversité de BordeauxInternational Development Research Centre
KeywordsBridging (networking)Latin AmericansPedagogySociologyPolitical scienceMathematics educationEconomic growthPsychologyEconomics

Abstract

fetched live from OpenAlex

This paper investigates empirically the role of child characteristics, household and territorial circumstances in shaping parents’ educational aspirations and expectations for their children, and the alignment or gap between the two. It focuses on higher education and makes three main contributions to the literature. First, it expands the geographical focus of existing research, comparing Chile, Colombia and Mexico within the same study design and sampling frame. Second, it focuses on intermediate territories, that is, a functionally integrated group of municipalities comprising an urban core between approximately 15,000 and 380,000 inhabitants and its hinterland. Third, it studies the influence of context beyond children’s school or neighbourhood, analysing territorial characteristics as the broader environment that frames a person’s preferences and ideas about life. The findings show that parents’ socioeconomic status and territorial characteristics are the key determinants of aspirations, expectations, and the feasibility gap in the three countries. This suggests that individual-level policies to increase household resources may not be sufficient for increasing educational aspirations, expectations and outcomes, unless combined with policies to increase local opportunities and reduce territorial inequalities.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.481
Threshold uncertainty score0.476

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.040
GPT teacher head0.393
Teacher spread0.353 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2025
Admission routes1
Has abstractyes

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