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Record W4415575728 · doi:10.25144/14601

EVALUATING THE RESTORATIVE POTENTIAL OF CHURCH BUILDINGS

2023· article· W4415575728 on OpenAlexaffabout
Josée Laplace, Catherine Guastavino

Bibliographic record

Venuenot available
Typearticle
Language
FieldEarth and Planetary Sciences
TopicBuilding materials and conservation
Canadian institutionsCentre for Interdisciplinary Research in Music Media and Technology
Fundersnot available
KeywordsWork (physics)Government (linguistics)Field (mathematics)Action (physics)

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, commented walks, 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 questionnaire results with regards to situational factors, items wording and procedure that may affect the ratings, with the complements of the qualitative methods used to provide a better understanding of people's experiences with church interiors.At a theoretical level, we report how the findings provide grounds to revisit the Biophilia hypothesis, in interior space with very little natural elements.At a practical level, we discuss how the research design can contribute to a broader discussion on the future of redundant churches.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.520
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.089
GPT teacher head0.325
Teacher spread0.236 · 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

Citations1
Published2023
Admission routes2
Has abstractyes

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