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Service-learning under COVID-19: A scoping review of the challenges and opportunities for practicing service-learning in the ‘New Normal’

2023· review· en· W4376865342 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Educational Development · 2023
Typereview
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsService-learningCoronavirus disease 2019 (COVID-19)ScholarshipService (business)Public relationsThematic analysisSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Political scienceBusinessPsychologySociologyMedicineQualitative researchPedagogyMarketingDiseaseSocial scienceInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Service-learning collaborations have the potential to effectively respond to community needs, students' needs, and institutional priorities. However, natural and man-made crises oftentimes throw these arrangements into disarray. The coronavirus (COVID-19) is one such significant crisis that continues to challenge service-learning collaborations worldwide. Based on a systematic scoping review of scholarship on service-learning programs conducted during COVID-19, this study aimed to explore thematic similarities and differences between them, elucidating key observations and insights for future action. Overall, findings from 13 peer-reviewed articles indicated that, although not immune to the wide-ranging adverse effects of COVID-19, service-learning has proven itself to be an effective responsive pedagogy in times of crisis.

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.

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)0.008
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.745
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.377
GPT teacher head0.480
Teacher spread0.103 · 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