MétaCan
Menu
Back to cohort
Record W2890456972 · doi:10.1177/1468797617723764

Curating the aural cultures of the Battery: Soundwalking, auditory tourism and interactive locative media sound art

2017· article· en· W2890456972 on OpenAlexfundaboutno aff
Kate Galloway

Bibliographic record

VenueTourist Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsnot available
FundersArts and Humanities Research CouncilMemorial University of NewfoundlandCanada Council for the Arts
KeywordsSoundscapeMateriality (auditing)EthnographySound (geography)Visual artsSociologyTourismSound artMedia studiesAestheticsHistoryArtAcousticsAnthropology

Abstract

fetched live from OpenAlex

Inside Outside Battery is a mobile media sound art installation for smartphone technologies that uses global positioning system (GPS) locative software to narrate walking visitors through the Battery, a heritage neighbourhood of St. John’s (Newfoundland, Canada). Auditory tourists, or soundwalkers, come to know the aural cultures of the Battery through the dynamic interactions of sound and place using site- and time-specific archival materials, stories, soundscapes, and expressive culture sourced from the Battery that play alongside real-time encounters with the physical and sonic materiality of the Battery. Employing practice-based ethnography, this article examines how site- and time-specific soundscape interactive documentary technologies engage socioenvironmental knowledge and foster a sense of place attachment for visitors to the Battery.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.012
Scholarly communication0.0060.003
Open science0.0010.005
Research integrity0.0010.001
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 head0.043
GPT teacher head0.378
Teacher spread0.335 · 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 designQualitative
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

Citations9
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueTourist StudiesSame topicGeographies of human-animal interactionsFrench-language works237,207