Installing Noise Activated Warning Signs in Library Quiet Spaces Does Not Appear to Reduce Actual or Perceived Noise Levels
Notice bibliographique
Résumé
A Review of: Lange, J., Miller-Nesbitt, A., & Severson, S. (2016). Reducing noise in the academic library: The effectiveness of installing noise meters. Library Hi Tech, 34(1), 45-63. https://doi.org/10.1108/LHT-04-2015-0034 Abstract Objective – To explore if installing noise activated warning signs (NoiseSigns) in library quiet spaces decreases perceived and actual noise levels. Design – Noise monitoring and user surveys (print and online). Setting – A large university in Canada. Subjects – Users of library quiet spaces where NoiseSigns have, and have not, been installed. Methods – NoiseSigns provide a visual cue informing those present when noise levels exceed a pre-determined level. In this study, researchers installed two NoiseSigns in quiet study spaces previously identified as having the “biggest noise issues” (p. 51), and set the devices to illuminate when noise levels exceeded 65 dB. User surveys investigated respondents’ perceived and desired noise levels via Likert scales before and after NoiseSigns were installed. Actual noise level measurements (via an iPad app) and headcounts were taken manually twice daily for 60 seconds during the same study phases. Additionally, the NoiseSigns recorded noise levels after they were installed. In order to account for variation in library usage over time, control data was also collected in other spaces, where NoiseSigns had not been installed. Main results – A total of 96 surveys were completed and analyzed across all study locations and time periods. One-way ANOVA tests showed there to be no significant difference in perceived noise levels after installing NoiseSigns in any of the intervention areas, in neither the short- or long-term. Respondents’ comments suggested much of the undesired noise originated from social areas adjacent to the quiet study zones or was of a type which would not set off the NoiseSigns (e.g., “people chew[ing] too loud[ly]” (p. 54)). One-way ANOVA tests also found there to be no significant difference in actual noise levels in any of the intervention areas after device installation. Data logging from the NoiseSigns themselves showed the “majority” (p. 56) of noise measurements were in the vicinity of 45-50 dB and “very rarely” (p. 56) did noise levels exceed the 65 dB threshold. Despite this, survey respondents appeared to be unhappy with noise, with mean desired noise levels being lower than those perceived. Conclusion – As a result of the study, the library now strives to have greater delineation between quiet and social spaces. They also seek to ensure doors between these areas are kept closed where possible. Additionally, the authors suggest libraries install noise activated warning signs in social spaces adjacent to quiet study zones in order to keep these spaces from becoming noisy enough to affect nearby quiet zones. Future research could look at the effect of different monitoring options (e.g., security guards, student self-monitoring) and various furniture arrangements on noise levels in the library.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,029 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,013 | 0,004 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».