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Record W1914812737 · doi:10.24908/pceea.v0i0.5733

HOMES OF HOPE: VISUALIZING SOCIAL RESPONSIBILITY

2015· article· en· W1914812737 on OpenAlexafffundvenue
Lauren Jatana Vathje, Marjan Eggermont, Robert W. Brennan

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsUniversity of Calgary
FundersSuncor Energy Incorporated
KeywordsSocial responsibilityQuality (philosophy)Work (physics)PsychologyKey (lock)Test (biology)Engineering ethicsKnowledge managementEngineeringPublic relationsComputer sciencePolitical scienceEcology

Abstract

fetched live from OpenAlex

A sense of professional social responsibilityis a key quality for engineers of the 21st century.Community Engaged Learning (CEL) is an excellent wayto develop social responsibility (SR) in students. But,there is a need to better understand how different typesCEL experiences impact SR development. Recently, apsychological framework and survey has been createdthat addresses how SR develops in engineers. We putthese SR tools to the test, along with some othermeasures, to see how a short-term international CELexperience impacted the students’ SR development.This study was of an exploratory nature to see how to bestwork with the new psychological framework and othermeasures of SR. All indicators showed that the short terminternational CEL had a positive impact on SRdevelopment and the SR tools proved to be useful ininterpreting and visualizing the impact on students. Ourfuture work aims to conduct many studies like this, to seeif we can understand how different types of CEL relate todevelopment of different areas of SR in students.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.366
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.028
GPT teacher head0.297
Teacher spread0.269 · 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

Citations0
Published2015
Admission routes3
Has abstractyes

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