Bibliographic record
Abstract
What is chance? How is it defined? And what do the definitions say about who makes them? These are some initial questions to be given an arena in the Happenstance Shelter [Abrigo do Acaso] – artistic project. As chance is subordinated, in everyday life, to an event in simultaneous space and time that causes change in the expected sequence of previous events, this paper aims to reflect on the project options for the architectural and aesthetic reconstruction of a physical place (at Canada da Cortinha nº0, Carrazedo, Bragança, Portugal) in order to constitute the scenography of this Happenstance Shelter and by doing so, to lead us to think about our understanding of time and space. In this sense, the body’s relationship with time and space – through memory, unpredictability, and transcendence – has been used as a bellwether to design an unexpected and unsettling atmosphere that interrogates the very existence of chance and the laws that govern life. More than conclusions, at the end of the paper, the expectations raised by the project under development are explained, which result from giving rise to the individual subjectivity of future participants in their human attempt to map, understand, and explain these cuts of reality that they experience with intrigue and to which they give the name of chance.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.039 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".