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Record W2547335519

A Habitat for Humanity and University Partnership: Enhancing on International Experiential Learning in El Salvador

2016· article· en· W2547335519 on OpenAlexaffabout
Robert Feagan, Mike Boylan

Bibliographic record

VenueArchivaria (Association of Canadian Archivists) · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsGeneral partnershipExperiential learningHumanityContext (archaeology)Meaning (existential)Service-learningPrivilege (computing)SociologyPedagogyPublic relationsEngineering ethicsPolitical sciencePsychologyEngineeringGeography
DOInot available

Abstract

fetched live from OpenAlex

The increase in international experiential learning (IEL hereafter) opportunities being developed by universities in the global north requires more attention both generally and with regards to specific IEL programming objectives. This paper provides observations and assessment of a case study of university-student participation in home-builds in El Salvador over the course of three years – a partnership between Habitat for Humanity and a Canadian university. The information collected is assessed relative to the key critiques and to the recommendations advocated in the IEL literature, with the intention of incorporating these critiques and recommendations in future IEL planning for this partnership, and to inform IEL work more generally. The key observations and recommendations include the need for enhanced student preparation pre and post-trip – meaning ‘critical reflection’ processes and materials on privilege and personal goals themes; on specific global south context; and enhancing on intercultural learning and awareness activities and processes e.g., more closely integrated host-community and participant relationship-building opportunities. These recommendations are seen as important for enhancing on this specific IEL program and its short-duration time-frame, while suggesting useful guideposts for IEL more generally, as its occurrence increases within the university setting.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.757
Threshold uncertainty score0.961

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.019
GPT teacher head0.281
Teacher spread0.262 · 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 designTheoretical or conceptual
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
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueArchivaria (Association of Canadian Archivists)Same topicInternational Student and Expatriate ChallengesFrench-language works237,207