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Record W2332257398 · doi:10.1386/ctl.10.2.143_1

Close encounters of the Other kind: Ethical relationship formation and International Service Learning education

2015· article· en· W2332257398 on OpenAlexaff
Allyson Larkin

Bibliographic record

VenueCitizenship Teaching and Learning · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicTourism, Volunteerism, and Development
Canadian institutionsThe King's University
Fundersnot available
KeywordsTransformative learningPrivilege (computing)SociologyService-learningInjusticePovertyPower (physics)PedagogyPublic relationsPolitical sciencePsychologySocial psychologyLaw

Abstract

fetched live from OpenAlex

Abstract International Service Learning (ISL) is a pedagogy designed to engage students in first-hand experiences of global social issues including poverty and inequality. There are growing concerns in the critical ISL research literature that positions of power and privilege obstruct opportunities to engage in transformative learning. Critiques are often founded on an understanding of ISL as learning about Others versus learning from Others and engaging with difference. This article considers the possibilities for a practice of ISL education that centres on the formation of socially ethical engagements with Others. It is motivated by my research on the impact of ISL practices on host communities in Tanzania. Racial and socio-economic differences are two key tensions that emerged as participants and community partners struggled to understand their respective roles in this project. Todd’s work problematizes ethical educational practices and is a valuable lens through which think about the ways that ISL may be complicit with the injustice that most practitioners and students of ISL originally seek to mitigate. Todd’s analysis built on Levinasian theory of relationship with Others is a space for ISL educators to imagine new opportunities for transformative and ethical educational practices.

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)0.004
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.234
Threshold uncertainty score0.766

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.040
GPT teacher head0.322
Teacher spread0.283 · 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 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

Citations6
Published2015
Admission routes1
Has abstractyes

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