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Record W2625600594 · doi:10.15402/esj.v2i2.172

Engaging Student Mothers Creatively: Animated Stories of Navigating University, Inner City, and Home Worlds

2017· article· en· W2625600594 on OpenAlexvenueaboutno aff
Lise Kouri, Tania Guertin, Angel Shingoose

Bibliographic record

VenueEngaged Scholar Journal Community-Engaged Research Teaching and Learning · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsnot available
Fundersnot available
KeywordsOutreachInner citySociologyGeneral partnershipAnimationNarrativePovertyPedagogyMedia studiesVisual artsPolitical scienceArt

Abstract

fetched live from OpenAlex

The article discusses a collaborative project undertaken in Saskatoon by Community Engagement and Outreach office at the University of Saskatchewan in partnership with undergraduate student mothers with lived experience of poverty. The results of the project were presented as an animated graphic narrative that seeks to make space for an under-represented student subpopulation, tracing strategies of survival among university, inner city and home worlds. The innovative animation format is intended to share with all citizens how community supports can be used to claim fairer health and education outcomes within system forces at play in society. This article discusses the project process, including the background stories of the students. The entire project, based at the University of Saskatchewan, Community Engagement and Outreach office at Station 20 West, in Saskatoon’s inner city, explores complex intersections of racialization, poverty and gender for the purpose of cultivating empathy and deeper understanding within the university to better support inner city students. amplifying community voices and emphasizing the social determinants of health in Saskatoon through animated stories.

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)0.687
metaresearch head score (Gemma)0.347
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.635
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.6870.347
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.6370.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0000.402
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 head0.151
GPT teacher head0.436
Teacher spread0.284 · 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 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

Citations2
Published2017
Admission routes2
Has abstractyes

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