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Record W2978671316 · doi:10.24908/ijesjp.v7i1.13568

Integrating Social Justice and Political Engagement into Engineering

2020· article· en· W2978671316 on OpenAlexvenueno aff
Skye Niles, Shawhin Roudbari, Santina Contreras

Bibliographic record

VenueInternational Journal of Engineering Social Justice and Peace · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCareer Development and Diversity
Canadian institutionsnot available
Fundersnot available
KeywordsSociotechnical systemCognitive reframingSocial engineering (security)Engineering ethicsSociologyPoliticsExpeditingField (mathematics)MeritocracyPublic relationsPolitical scienceEnvironmental ethicsEngineeringLawSocial psychologyManagementPsychologyComputer securityEconomics

Abstract

fetched live from OpenAlex

Many engineering activists have emphasized the need to reframe engineering as a sociotechnical field in order to expand engineers' contributions to social justice and peace. Yet, reframing engineering as sociotechnical does not always lead to critical engagement with social justice. We provide several examples of how “social” aspects have been brought into engineering in a depoliticized manner that limits engagement with political and social justice goals. We link these examples to Cech’s three pillars of the “culture of disengagement” in engineering: social/technical dualisms, meritocracy, and depoliticization. We argue that reframing engineering as sociotechnical addresses the first pillar, the social/technical dualism, but does not necessarily include the second and third pillars. We propose that all three pillars can be addressed through integrating explicit attention to political engagement and social justice in efforts to reframe engineering as a sociotechnical field. Doing so can increase engineers’ capacity to contribute to social justice and peace.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.665
Threshold uncertainty score0.497

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.028
GPT teacher head0.298
Teacher spread0.270 · 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 designNot applicable
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

Citations19
Published2020
Admission routes1
Has abstractyes

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