Allometric scaling and accidents at work
Allometry is the knowledge concerning relations between the features of some beings, like animals, or cities. For example, the daily energy rate is proportional to a mass of mammals rise of 3/4. This way of thinking has spread quickly from biology to many areas of research concerned with sociotechni...
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| Format: | Online |
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Taylor & Francis
2016
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4867905/ |
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pubmed-48679052016-05-23 Allometric scaling and accidents at work Cempel, Czesław Tabaszewski, Maciej Ordysiński, Szymon Articles Allometry is the knowledge concerning relations between the features of some beings, like animals, or cities. For example, the daily energy rate is proportional to a mass of mammals rise of 3/4. This way of thinking has spread quickly from biology to many areas of research concerned with sociotechnical systems. It was revealed that the number of innovations, patents or heavy crimes rises as social interaction increases in a bigger city, while other urban indexes such as suicides decrease with social interaction. Enterprise is also a sociotechnical system, where social interaction and accidents at work take place. Therefore, do these interactions increase the number of accidents at work or, on the contrary, are they reduction-driving components? This article tries to catch such links and assess the allometric exponent between the number of accidents at work and the number of employees in an enterprise. Taylor & Francis 2016-04-02 2016-04-01 /pmc/articles/PMC4867905/ /pubmed/26655044 http://dx.doi.org/10.1080/10803548.2015.1131071 Text en © 2016 Central Institute for Labour Protection – National Research Institute (CIOP-PIB). Published by Taylor & Francis. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/Licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. |
| repository_type |
Open Access Journal |
| institution_category |
Foreign Institution |
| institution |
US National Center for Biotechnology Information |
| building |
NCBI PubMed |
| collection |
Online Access |
| language |
English |
| format |
Online |
| author |
Cempel, Czesław Tabaszewski, Maciej Ordysiński, Szymon |
| spellingShingle |
Cempel, Czesław Tabaszewski, Maciej Ordysiński, Szymon Allometric scaling and accidents at work |
| author_facet |
Cempel, Czesław Tabaszewski, Maciej Ordysiński, Szymon |
| author_sort |
Cempel, Czesław |
| title |
Allometric scaling and accidents at work |
| title_short |
Allometric scaling and accidents at work |
| title_full |
Allometric scaling and accidents at work |
| title_fullStr |
Allometric scaling and accidents at work |
| title_full_unstemmed |
Allometric scaling and accidents at work |
| title_sort |
allometric scaling and accidents at work |
| description |
Allometry is the knowledge concerning relations between the features of some beings, like animals, or cities. For example, the daily energy rate is proportional to a mass of mammals rise of 3/4. This way of thinking has spread quickly from biology to many areas of research concerned with sociotechnical systems. It was revealed that the number of innovations, patents or heavy crimes rises as social interaction increases in a bigger city, while other urban indexes such as suicides decrease with social interaction. Enterprise is also a sociotechnical system, where social interaction and accidents at work take place. Therefore, do these interactions increase the number of accidents at work or, on the contrary, are they reduction-driving components? This article tries to catch such links and assess the allometric exponent between the number of accidents at work and the number of employees in an enterprise. |
| publisher |
Taylor & Francis |
| publishDate |
2016 |
| url |
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4867905/ |
| _version_ |
1613579646709792768 |