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Record W4416697907 · doi:10.1145/3773967.3773977

Enabling Synchronous Hybrid Participation at Assets 2024

2025· article· en· W4416697907 on OpenAlex
Oliver Alonzo, Emma J. McDonnell, Jesse J. Martinez, Jay Henderson

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

VenueACM SIGACCESS Accessibility and Computing · 2025
Typearticle
Languageen
FieldDecision Sciences
TopicScientific Computing and Data Management
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsAsynchronous communicationHybrid system

Abstract

fetched live from OpenAlex

The ACM ASSETS conference is the premier venue for accessible computing research, and it is dedicated to providing access to all attendees. At ASSETS 2024 we were determined to establish a hybrid conference to provide synchronous access to remote attendees, which served as an accessible option for community members who were not attending in-person. This newsletter article details our hybrid setup, which consisted of Zoom, Discord, and YouTube. Combining these tools enabled both synchronous and asynchronous participation across different tracks. Our model was well received by the community. We hope that sharing our setup can be a valuable contribution towards more robust synchronous, accessible, and integrated hybrid conference experiences.

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)0.008
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.716
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0020.007
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 head0.103
GPT teacher head0.430
Teacher spread0.327 · 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