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Record W3198371082 · doi:10.53956/jfde.2021.159

Choice With(out) Equity? Family Decisions of Child Return to Urban Schools in Pandemic

2021· article· en· W3198371082 on OpenAlexaff
Robert Cotto, Sarah L. Woulfin

Bibliographic record

VenueJournal of Family Diversity in Education · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsTrinity College
Fundersnot available
KeywordsEquity (law)School choiceScholarshipPandemicClosure (psychology)PsychologySociologyPolitical scienceDemographic economicsPublic relationsEconomic growthCoronavirus disease 2019 (COVID-19)EconomicsMedicineLaw

Abstract

fetched live from OpenAlex

In response to the COVID-19 global pandemic, most schools across the country closed in-person instruction for a period of time and many shifted to online schooling. Beginning in fall 2020, schools around the United States began reopening and many districts offered families a decision or “choice” to return their children to an in-person or online schooling experience. In many cities, this approach complicated existing school choice and permanent closure policies with already existing equity issues. Building upon previous scholarship on school choice and closure, this study draws on the concept of school choice with(out) equity (Frankenberg et al., 2010; Scott & Stuart Wells, 2013; Horsford et al., 2019). Using data from an online survey (n = 155 participants) in August 2020, this study examines why families (50% white, 50% people of color) decided to return their children to in-person schooling in Hartford, Connecticut. This study uses a mixed-method analysis of qualitative responses and quantitative data to understand family decisions to return to in-person schooling (Creswell, 2014). Rather than school choices with full equity considerations during the pandemic, these family responses focused on needs of childcare for full-time work and health safety. These responses suggest a partial equity in the landscape of available choices. The study raises questions about reapplying old forms of school choice to a new form of temporary school closure during pandemic.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.125
GPT teacher head0.395
Teacher spread0.270 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations11
Published2021
Admission routes1
Has abstractyes

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