Bibliographic record
Abstract
RESEARCH BACKGROUND Public Announcements 2 contributes to the broad field of public art and the narrow field of audio artworks within the public domain. The peer community includes Ceal Floyer (UK) and collaborative duo Janet Cardiff and George Bures Miller (Canada). Key characteristics of this scholarly debate include sound works that enhance an experience of public space through their subject matter and surprising approach. This Creative work seeks to extend this field by using absurd humour to activate public space in unexpected ways. CONTRIBUTION This Creative work is framed by the following research question: How can humourous announcements interrupt passers-by and enhance an experience of public space? Dr Kosloff wrote and professionally recorded 30 spoken announcements. The announcements were broadcast intermittently from overhead speakers installed along the Arts Centre Melbourne’s covered walkway. The announcements explore quirky exchanges that often occur within the public domain, such as random thoughts, snippets of overheard conversation and unexpected interactions. The project investigates language, tone of voice and the performative context of public space. RESEARCH SIGNIFICANCE Public Announcements 2 was commissioned for the curated exhibition ‘Who’s Afraid of Public Space?’ held at the Australian Centre for Contemporary Art (ACCA) 2021-2022. The exhibition featured seminal artists, including Reko Rennie (Kamilaroi/Australia), Callum Morton (Australia), Eugenia Lim (Australia) and Field Theory collective (Australia). Dr Kosloff was interviewed about her project by Andrew Stephens for the Age newspaper on 17/12/21. She delivered a public talk at ACCA and was interviewed about the work for a short documentary. A comprehensive catalogue for the exhibition is also forthcoming.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.328 | 0.162 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".