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Record W4238561615 · doi:10.47678/cjhe.v49i1.188219

Bringing College Classrooms to the Community: Promoting Post-Secondary Access for Low-Income Adults Through Neighbourhood-Based College Courses

2019· article· en· W4238561615 on OpenAlexafffundvenue
Alan Bourke, Jim Vanderveken, Emily Ecker, Jeremy Atkinson, Natalie Shearer

Bibliographic record

VenueCanadian Journal of Higher Education · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Research Studies
Canadian institutionsMohawk College
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsNeighbourhood (mathematics)OutreachGeneral partnershipLow incomeCommunity collegeCommunity engagementSociologyPublic relationsPsychologyPedagogyMedical educationEconomic growthPolitical scienceEconomicsSocioeconomics

Abstract

fetched live from OpenAlex

In this paper we utilize interview data to explore the workings of a college– community partnership program that delivers tuition-free, for-credit courses to low-income adult students in neighbourhood-based settings. Addressing the interplay of individual and structural barriers on the educational readiness of students, our findings explore how the program builds participants’ confidence and self-belief, and how the neighbourhood-based delivery model encourages their engagement with post-secondary education (PSE). We find that the value of embedding PSE capacity and resources in low-income communities lies not only in its potential to engage adult learners, but also in how it nurtures a greater sense of community integration and social inclusion. We conclude by suggesting that our study provides a useful foundation for institutions elsewhere aiming to recalibrate and extend their community outreach strategies when seeking to promote post-secondary access and engagement for low-income populations.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.343
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.024
GPT teacher head0.367
Teacher spread0.343 · 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.

Study designNot applicable
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 routes3
Has abstractyes

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