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Record W72296954 · doi:10.17705/1thci.00022

A Call for Engaging Context in HCI/MIS Research with Examples from the Area of Technology Interruptions

2010· article· en· W72296954 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

VenueAIS Transactions on Human-Computer Interaction · 2010
Typearticle
Languageen
FieldDecision Sciences
TopicPersonal Information Management and User Behavior
Canadian institutionsMcGill University
Fundersnot available
KeywordsContext (archaeology)Set (abstract data type)Computer scienceTask (project management)Human–computer interactionKnowledge managementCore (optical fiber)Data scienceEngineeringSystems engineering

Abstract

fetched live from OpenAlex

This paper contributes to the discussion on future directions of Human-Computer Interaction in Information Systems (HCI/MIS) research by explicating the role of task- and social context. We show that context has not been sufficiently engaged, and argue why it is important to pay more attention to it in theory and design of future HCI/MIS research. Drawing on examples from the core HCI area of technology interruptions, we formulate a set of general research questions and guidelines, which allow us to represent the context of multiple users in continuous collaboration with multiple tools while working on tasks that are intertwined within business processes. These guidelines will generate new insights for HCI/MIS research and allow us to develop research that captures the changing nature of the computing environment.

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 score0.945
Threshold uncertainty score0.581

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.533
GPT teacher head0.511
Teacher spread0.023 · 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