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Record W4320734269 · doi:10.3397/in_2022_0758

Evaluating the restorative potential of church buildings

2023· article· en· W4320734269 on OpenAlexaffabout
Josée Laplace, Catherine Guastavino

Bibliographic record

VenueNOISE-CON proceedings · 2023
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsMcGill University
Fundersnot available
KeywordsSoundscapeOperationalizationContext (archaeology)Field (mathematics)Intersection (aeronautics)AestheticsArchitectural engineeringSociologySound (geography)HistoryGeographyEngineeringEpistemologyArtArchaeologyCartographyAcoustics

Abstract

fetched live from OpenAlex

We report the preliminary results of a study on the experience of soundscape and architectural ambiances of church buildings, with an emphasis on their restorative qualities. Through questionnaires, soundwalks and interviews with 16 diverse participants, we aim to characterize the sensory qualities of 2 contrasting church buildings in Montreal. Our data collection instruments operationalize concepts at the intersection of different research fields: soundscapes, attention restoration, quiet areas, architectural ambiances and heritage (including religious) places. As such, it encompasses a broad range of descriptors and outcomes. At a methodological level, we discuss the relative contributions of the different methods used and how they complement one another to provide a better understanding of experiences of church interiors. At a theoretical level, we report the main findings in term of experiences of space, sound, ambiance and associated benefits. In particular, we discuss the restorative potential of church building(s) and questions raised in relation to the particular context of this field work.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.611
Threshold uncertainty score0.695

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.110
GPT teacher head0.462
Teacher spread0.352 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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 routes2
Has abstractyes

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