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Record W7116643318

Archiving Memories through Art - Dinner Among Five People on 26th May, a biannual documentary project initiated by Boie Wog and Sam Tam

2023· other· en· W7116643318 on OpenAlexaboutno aff
Sing Hang Tam, Wog Boie

Bibliographic record

VenueUniversity of the Arts London Research Online (University of the Arts London) · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsExhibitionDocumentationHappeningIdeologyWork (physics)
DOInot available

Abstract

fetched live from OpenAlex

Dinner Among Five People on 26th May is a documentary that records several dinner gatherings among five young adults who are from Hong Kong. It takes place once every two years, always on the same date. The participants are individuals who have, in various ways, participated in the pro-democracy movements in Hong Kong from 2012 to now. Throughout the dinners, they would recall fragmented memories of what had happened in Hong Kong in recent years and discuss the current situation and plans for the future. Each gathering lasts roughly two hours, and the conversations among them grow naturally without planned agendas. This work, initiated by Boie Wog and Sam Tam, is a long-term one that has been running biannually since mid-2017. Over the span of 6 years, from 2017 to 2019, four sets of documentation have been completed; the project is aimed to be carried out for at least 20 years. The first version of this work was exhibited in Network, an exhibition organised by RAGE Collective, which took place at MOVEMENT Worcester, United Kingdom, in 2017. The work has also been exhibited in other parts of the UK, Canada, and Korea in museums, art galleries, and art spaces. It has received media and press coverage in various parts of the world. The hosts have also been invited to speak about the ideology of the project in public lectures, conferences, and artists’ talks.

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)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.020
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0060.002
Scholarly communication0.0070.004
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0190.007

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 head0.044
GPT teacher head0.300
Teacher spread0.256 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2023
Admission routes1
Has abstractyes

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