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Record W4383652409 · doi:10.1145/3563703.3591458

Beyond Academic Publication: Alternative Outcomes of HCI Research

2023· article· en· W4383652409 on OpenAlexafffund
MinYoung Yoo, Arne Berger, Joseph Lindley, David Philip Green, Yana Boeva, Iohanna Nicenboim, William Odom

Bibliographic record

VenueDesigning Interactive Systems Conference · 2023
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsSimon Fraser University
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsConversationOpenness to experienceExhibitionDisseminationComicsAcademic communityComputer sciencePsychologyVisual artsLibrary scienceSocial psychology

Abstract

fetched live from OpenAlex

In the HCI community, there is more openness and interest toward different forms of research outcomes beyond written academic publications. These include pictorial papers, video/audio documentaries, public exhibitions, posters and brochures, design fiction, comics, podcasts and many more. These alternative research outcomes play a critical role in explaining, disseminating, and translating valuable insights and knowledge from HCI research to people outside academic communities. We propose this workshop to initiate the conversation among researchers in the DIS community in generating alternative forms of research outcomes. What inspirations, motivations and critical factors influence the creation of alternative research outcomes? Who is the main audience, and what are the barriers and limitations of making them? The outcome of the workshop will be an enhanced understanding related to how HCI knowledge can be translated to or created for different audiences outside of academia, and a guide for HCI researchers towards creating alternate research outcomes.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.303
metaresearch head score (Gemma)0.390
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.697
Threshold uncertainty score0.859

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3030.390
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0130.018
Science and technology studies0.0160.040
Scholarly communication0.0600.055
Open science0.0060.036
Research integrity0.0090.012
Insufficient payload (model declined to judge)0.0190.004

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 head0.194
GPT teacher head0.423
Teacher spread0.230 · 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

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designTheoretical or conceptual
DomainEvaluation
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2023
Admission routes2
Has abstractyes

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