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Record W2037133877 · doi:10.1016/j.intcom.2006.07.005

Are interface agents scapegoats? Attributions of responsibility in human–agent interaction

2006· article· en· W2037133877 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInteracting with Computers · 2006
Typearticle
Languageen
FieldComputer Science
TopicAI in Service Interactions
Canadian institutionsLakehead University
Fundersnot available
KeywordsAttributionInterface (matter)AutonomyComputer scienceHuman–computer interactionSoftware agentSocial psychologyPsychologyArtificial intelligence

Abstract

fetched live from OpenAlex

Journal Article Are interface agents scapegoats? Attributions of responsibility in human–agent interaction Get access Alexander Serenko Alexander Serenko * Faculty of Business Administration, Lakehead University, 955 Oliver Road, Thunder Bay, Ont., Canada P7B 5E1 * Tel.: +1 807 343 8698; fax: +1 807 343 8443. E-mail address:aserenko@lakeheadu.ca Search for other works by this author on: Oxford Academic Google Scholar Interacting with Computers, Volume 19, Issue 2, March 2007, Pages 293–303, https://doi.org/10.1016/j.intcom.2006.07.005 Published: 12 September 2006 Article history Received: 26 July 2005 Revision received: 25 July 2006 Accepted: 26 July 2006 Published: 12 September 2006

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.230
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.001
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 head0.034
GPT teacher head0.325
Teacher spread0.291 · 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