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Record W2610506029 · doi:10.1145/3027063.3051135

Research Ethics in HCI

2017· article· en· W2610506029 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
Fundersnot available
KeywordsMeaning (existential)Engineering ethicsDiversity (politics)Field (mathematics)SociologyInformed consentStyle (visual arts)Information ethicsResearch ethicsEthics of technologyComputer sciencePsychologyEngineeringMeta-ethics

Abstract

fetched live from OpenAlex

As interactive technologies evolve and reach into every aspect of modern life, research practices in human-computer interaction (HCI) have changed. The methodological and epistemological foundations of the field are shifting to reflect the diversity of contexts in which rapidly changing digital technology is being used. Alongside these changes, new ethical challenges emerge for the HCI community, both in terms of research ethics and responsible research and innovation. Open dilemmas include issues such as the shifting meaning of informed consent, anonymisation or privacy in an always-online world. The SIGCHI Ethics Committee has been established to look into the processes, practices and structures at SIGCHI venues to deal with such ethical dilemmas and how they can be addressed in a transparent, consistent and open way. This town hall style panel will be an opportunity to prompt community discussion and collect input into how we can further address these challenges.

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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.749
Threshold uncertainty score0.593

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.001
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 head0.397
GPT teacher head0.544
Teacher spread0.148 · 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

Citations43
Published2017
Admission routes1
Has abstractyes

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