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Record W6986387398

Performing with Technology

2023· article· en· W6986387398 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotanical Studies and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsHumanityLonelinessSound (geography)GentrificationSet (abstract data type)
DOInot available

Abstract

fetched live from OpenAlex

This article departs from an intermedial theatre production and an acousmatic sound performance. In these productions the use of audio and video technology was central to mediate a manifold of perspectives on societal challenges concerning migration and xenophobia. The multi-channel radiophonic composition Karlskrona/Malmö (2017), revolved around the fictional murder of a left-wing activist. The performance was produced at the same time as several notable violent right-wing hate crimes took place in Sweden. Quite a few detention centres were set on fire in different places in Sweden, in Kärrtorp, a suburb of Stockholm, alt-right activists attacked a peaceful demonstration, and in Malmö, a well-known activist was beaten down by neo-Nazis. Our other example, Arrival Cities: Malmö (2013), was inspired by the book Arrival City (2010) by the Canadian journalist Doug Saunders which described the cities that have become ports for the people who have migrated. According to Saunders, these cities are places of loneliness and misery but at the same time dynamic focal points for the transformation of most of humanity from rural to urban citizens. The performance combined theatre with chamber- and electro-acoustic music and portrayed the migrant situation in Sweden a few years before the migrant wave hit Europe in 2015 and many countries closed their borders.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.432
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.265
GPT teacher head0.519
Teacher spread0.254 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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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