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Record W2307254767

How Young Adults Perceive Their Rural Ohio Communities

2014· article· en· W2307254767 on OpenAlexvenueno aff
Greg Homan, Jason Hedrick, Jeff Dick, Mark Light

Bibliographic record

VenueJournal of rural and community development · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsRespondentCommunity collegeRural areaRural communitySocioeconomicsGeographyPerceptionEntertainmentCommunity educationPsychologyPolitical scienceSociologyMedicineMedical educationPedagogy
DOInot available

Abstract

fetched live from OpenAlex

This study analyzes the trends and issues related to the retention of young adults in Northwest Ohio. Researchers sampled over 340 young adults (25-34 years of age) from 8 counties in Northwest Ohio. Results highlight rural community perceptions of young adults as well as those factors that impact the decision to remain in Rural Northwest Ohio. Sampled adults report generally favorable impressions of the area with emphasis on the quality of schools, community safety, and affordability of the area. Overall lower ratings were revealed on components related to cultural, entertainment, and employment opportunities in the area. Respondents with higher incomes and those with stronger Northwest Ohio roots, i.e., who were themselves raised in Northwest Ohio along with their parents, were more likely to feel positively about Northwest Ohio's economic outlook and the community's strength. In addition, the higher the respondent's education, the more likely they were to react positively regarding the community's strength/safety. Young adults reported that parents were a strong influence on their decision to return or remain in their rural communities. Keywords: youth, community, development, career, retention

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.033
GPT teacher head0.286
Teacher spread0.253 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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