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Record W2590306122 · doi:10.1177/0092055x17694908

Hosting a Tent City: Student Engagement and Homelessness

2017· article· en· W2590306122 on OpenAlexaboutno aff
Jennifer McKinney, Karen A. Snedker

Bibliographic record

VenueTeaching Sociology · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsnot available
Fundersnot available
KeywordsSociologyPovertyQuarter (Canadian coin)Service-learningSocial workInequalityPedagogyGender studiesEconomic growthGeography

Abstract

fetched live from OpenAlex

In response to increasing homelessness in our city, Seattle Pacific University invited a homeless encampment (Tent City) to reside on our university campus for three months. This provided an opportunity to engage students on issues of poverty and inequality. Building from a service-learning model, we devised course work around homelessness and applied research. Students took a two-quarter course sequence to become knowledgeable about homelessness and sociological research methods in order to collect field observations and conduct interviews with Tent City residents. Based on student reflections, stereotypes about homelessness were challenged and social distance between students and people who were homeless was reduced. Student exposure to homelessness through faculty-guided research is an effective tool in developing a sociological imagination and an important step in fostering agents of social change.

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)0.003
metaresearch head score (Gemma)0.007
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.003
Scholarly communication0.0050.002
Open science0.0010.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.114
GPT teacher head0.462
Teacher spread0.348 · 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

Citations16
Published2017
Admission routes1
Has abstractyes

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