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Record W4405438263 · doi:10.1145/3708907.3708908

Equity, Diversity and Inclusion at ACM MMSys 2023

2023· article· en· W4405438263 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

VenueACM SIGMultimedia Records · 2023
Typearticle
Languageen
FieldComputer Science
TopicInformation Systems Education and Curriculum Development
Canadian institutionsUniversity of OttawaSimon Fraser University
Fundersnot available
KeywordsComputer scienceEquity (law)Inclusion (mineral)Diversity (politics)ChemistryLawPolitical science

Abstract

fetched live from OpenAlex

The 14th ACM Multimedia Systems Conference (MMSys 2023) took place from June 7-10, 2023 in Vancouver, Canada. To continue the significant efforts from the last years, and building on the strong commitment of the MMSys community to create a diverse, inclusive and accessible forum to discuss advancements in the area of multimedia systems and the technology experiences they enable, several EDI measures were adopted. The main goals were to (1) raise awareness around the importance of diversity and inclusion for both the MMSys community and the research fields represented at MMSys and (2) to enable diverse participation and inclusion of underrepresented groups. In this column, we provide a brief overview of the main EDI activities and a number of key numbers, as well as short testimonials from two participants.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Open science, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.371
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.000
Scholarly communication0.0000.001
Open science0.0020.170
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.046
GPT teacher head0.302
Teacher spread0.255 · 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