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Record W2007460187 · doi:10.1093/iwc/iwt026

Introduction to the Special Issue: The Tricky Landscape of Developing Rating Scales in HCI

2013· article· en· W2007460187 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

VenueInteracting with Computers · 2013
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsCarleton University
Fundersnot available
KeywordsUsabilityComputer scienceConstruct (python library)Product (mathematics)Human–computer interactionMathematicsProgramming language

Abstract

fetched live from OpenAlex

The official imprimatur for including usability questionnaires within HCI came with the genesis of the ISO 9241 Part 11 definition of usability, which included ‘satisfaction’ as an aspect of usability—a definition that sat perhaps rather uneasily with the objective, Taylorist (Taylor, 1911) definitions of ‘efficiency’ and ‘effectiveness’ (published as ISO, 1998, but existing in circulated official drafts for some years before): Satisfaction measures the extent to which users are free from discomfort and their attitudes towards the use of the product… [it] can be specified and measured by subjective rating on scales… That usability, or even user satisfaction could be considered to be a multi-dimensional subjective construct, had been suggested by Kirakowski and Corbett (1988) and brought out clearly (Kirakowski and Corbett, 1993).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.575
Threshold uncertainty score0.402

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.011
GPT teacher head0.254
Teacher spread0.243 · 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