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Record W2947898694 · doi:10.3968/10938

The Perceived Family and Parental Influence on African American Men Who Enroll in Community Colleges

2019· article· en· W2947898694 on OpenAlexvenueno aff
Iii David V. Tolliver, Kit Kacirek, Michael T. Miller

Bibliographic record

VenueCross-cultural communication · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMulticulturalismAfrican americanEthnic groupPsychologyHigher educationCommunity collegeGerontologyMedical educationSociologyPolitical sciencePedagogyMedicine

Abstract

fetched live from OpenAlex

Higher education institutions have generally been successful in increasing the number of diverse populations who attend college, especially recruiting and enrolling record numbers of Hispanic and Asian students. African American enrollments continue to lag behind these other diverse groups, with African American men being among the lowest of the multicultural groups to be enrolled in higher education today. Community colleges have been perhaps the most successful in recruiting and enrolling African American men, and the current study sought to describe how the families of these men interact and encourage or discourage enrollment. Using a series of semi-structured interviews, families were found to play a perceived important role in the decision to enroll in a community college. These families mentored the African American men in the study, created expectations for them to have successful life beyond high school, and pushed them to have positive ideas about their future and to plan for that future. These findings were consistent with modeling about college going decision-making, and also reinforced the emerging theory of community expectancy.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.004
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.029
GPT teacher head0.408
Teacher spread0.379 · 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; both teacher heads agree on what is shown here.

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
Published2019
Admission routes1
Has abstractyes

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