|Appears in Collections:||Faculty of Social Sciences eTheses|
|Title:||Trust in the data: External data use by the Scottish third sector|
social network analysis
|Publisher:||University of Stirling|
|Abstract:||This thesis investigates how the Scottish third sector engages with external data resources. The research is broken into two main strands. The first strand determines factors which affect the level of data use by charities. The second concerns the role of trust in third sector data use, in particular, what effect third sector use of data has on other users of data and the role data plays in society more generally. While the first of these strands is more pertinent to charities themselves, the second is particularly important in the wake of ‘Fake news’ and a general decline in trust for experts driven by misinformation online. Findings from this research show that there is a relatively low ability to use data among Scottish charities and many are resorting to pre-analysed, aggregate findings. Factors related to a low ability to use data include being a small charity, an old charity and a charity with a narrow focus. Analysis of a series of barriers and enablers found that barriers tend to inhibit data use altogether, where enablers tend to determine level of use. Support to help facilitate data use was then considered, finding that Twitter acts as a forum where support relationships develop between charities and infrastructure bodies, who share widely aimed, one-to-many tweets to support data use. The importance of infrastructure organisation became even more apparent when issues of trust were considered and found that, while charities trust data, they are less trusting of the interpretation which is laid over data and therefore they invest their trust in infrastructure organisations. Infrastructure organisations were found to have a healthy distrust of government data and are invested in feedback mechanisms where they correct mistakes in data and help increase the quality of, and trust in, Scottish Government data more generally.|
|Type:||Thesis or Dissertation|
|TomWallace_Thesis_normalmargins.pdf||Copy of PhD with non-mirrored margins||3.01 MB||Adobe PDF||Under Embargo until 2020-10-01 Request a copy|
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