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Record W1776559619 · doi:10.24908/pceea.v0i0.5732

ETHICS 2.0: AN INTROSPECTIVE APPROACH TO UNDERSTANDING AND TAKING OWNERSHIP OF YOUR ACTIONS

2015· article· en· W1776559619 on OpenAlexafffundvenue
Karim S. Karim

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicThe Impact of Diversity and Innovation on Society
Canadian institutionsUniversity of Waterloo
FundersUniversity of Waterloo
KeywordsIntrospectionEngineering ethicsIdentity (music)PsychologyFocus (optics)PedagogyMathematics educationSociologyEngineeringCognitive psychology

Abstract

fetched live from OpenAlex

ECE290 (Engineering Profession, Law andEthics) is a second year core course in the undergraduateElectrical and Computer Engineering program at theUniversity of Waterloo. This course was designed to moveaway from achieving desired ethical outcomes or “right”answers and instead to focus on refining individualdecision-making processes. Ethics was framed asstemming from the fundamental identity question faced byeach individual and the core beliefs held by the individualwith an aim to make the course more personal, engagingand introspective for the student. Students also gainedpractical experience in deconstructing their own identityby identifying and understanding master behavioralpatterns and the perspectives of various characters inpertinent literature and case studies where ethicalambiguity is at the forefront. Evaluation and testingmethods for the ethics component of the course weredesigned to focus on evaluating the depth and breadth ofthe students’ decision-making processes. Student courseevaluation questionnaires had a response rate of between60-75% and indicated that students strongly believed theywere being encouraged to think critically and reasonindependently

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.740
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
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 head0.170
GPT teacher head0.334
Teacher spread0.164 · 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

Citations0
Published2015
Admission routes3
Has abstractyes

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