Sounds of silence: data for analysing muted safety voice in speech

Transcribed text from simulated hazards contains important content relevant for preventing harm. By capturing and analysing the content of speech when people raise (safety voice) or withhold safety concerns (safety silence), communication patterns may be identified for when individuals perceive risk, and safety management may be improved through identifying potential antecedents. This dataset contains transcribed speech from 404 participants (n students = 377; n female = 277, Age M (sd) = 22.897 (5.386)) engaged in a simulated hazardous scenario (walking across an unsafe plank), capturing 18,078 English words (M (sd) = 46.117 (37.559)). The data was collected through the Walking the plank paradigm (Noort et al, 2019), which provides a validated laboratory experiment designed for the direct observation of communication in response to hazardous scenarios that elicit safety concerns. Three manipulations were included in the design: hazard salience (salient vs not salient), responsibilities (clear vs diffuse) and encouragements (encouraged vs discouraged). Speech between two set timepoints in the hazardous scenario was transcribed based on video recordings and coded in terms of the extent to which speech involved safety voice or safety silence. Files contain i) a.csv containing the raw data, ii) a.csv providing variable description, iii) a Jupyter notebook (v. 3.7) providing the statistical code for the accompanying research article, iv) a.html version of the Jupyter notebook, v) a.html file providing the graph for the.html Jupyter notebook, vi) speech dictionaries, and vii) a copy of the electronic questionnaire. The data and supplemental files enable future research through providing a dataset in which participants can be distinguished in terms of the extent to which they are concerned and raise or withhold this. It enables speech and conversation analyses and the Jupyter notebook may be adapted to enable the parsing and coding of text using provided, existing and custom dictionaries. This may lead to the identification of communication patterns and potential interventions for unmuting safety voice. This data-in-brief is published alongside the research article: M. C. Noort, T.W. Reader, A. Gillespie. (2021). The sounds of safety silence: Interventions and temporal patterns unmute unique safety voice content in speech. Safety Science

The sounds of safety silence: interventions and temporal patterns unmute unique safety voice content in speech

Research shows that withholding safety concerns on encountering hazards – safety silence – is a critical contributor to accidents. Studies therefore aim to prevent accidental harm through interventions for reducing safety silence. Yet, the behaviour remains poorly understood, obstructing effective safety management: it is unclear to what extent safety silence involves muted safety voice (the partial withholding of safety concerns), and how muted safety voice can be recognised in speech, may be measured based on the degrees and types of safety voice (speaking up about safety), progresses over time, and may be optimally reduced. To improve safety management, this study proposes a conceptual model for the manifestation of safety silence and muted safety voice using a laboratory experiment (N = 404) to evaluate the implications for the effectiveness of three interventions (salient hazards, clear responsibilities, encouragements) across stages of a hazard. Results indicated that safety silence and muted safety voice are measurable in terms of the degree to which concerned people engage in five types of safety voice at different points in time, and we revealed this is important for safety management: interventions only unmute safety voice at unique hazard stages and for knowledge-based speech when people are concerned. This indicates that safety silence and muted safety voice are situated and can be recognised in nuanced speech, with interventions being most effective when timed appropriately and people have safety concerns to speak up about

Zelfportret

Boven het 'zelfportret' van Arjen Boin in Bestuurskundige Berichten van april 1998 stond het woord 'Toeval' en dat predikaat is ook op mijn 'wetenschappelijke loopbaan' van toepassing. Bij toeval heb ik in 1975 gekozen voor de studie sociologie; eigenlijk had ik liever economie of politicologie gestudeerd, maar dan kon toen in Leiden niet. (Er was in die tijd evenmin een opleiding bestuurskunde, maar ik zou er in 1975 als 'socialistisch student' niet over gepiekerd hebben om daarvoor te kiezen.

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