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Record W2795415114 · doi:10.1145/3170427.3186321

Research Ethics for HCI

2018· article· en· W2795415114 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsUniversity of Toronto
FundersMicrosoft Research
KeywordsEngineering ethicsEthical issuesDisseminationDisciplinePanel discussionResearch ethicsSociologyFace (sociological concept)Public relationsPolitical scienceSocial scienceEngineeringBusinessLaw

Abstract

fetched live from OpenAlex

An ongoing challenge within the HCI research community is the development of community norms for research ethics in the face of evolving technology and methods. Building upon a successful town hall meeting at CHI 2017, this panel will include members of the SIGCHI Research Ethics Committee, but will be structured to facilitate a roundtable discussion and to collect input about current challenges and processes. The panel will pose open questions and invite audience discussion of best practices focused on issues such as cultural and disciplinary differences in ethical norms. There will also be discussion of how ethical issues are handled in SIGCHI paper submission and reviews, processes for how we might create and disseminate ethics resources, and regulatory issues such as the recent IRB changes for U.S. institutions.

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.

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)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.840
Threshold uncertainty score0.791

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.409
GPT teacher head0.538
Teacher spread0.129 · 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

Quick stats

Citations22
Published2018
Admission routes1
Has abstractyes

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