content(cms): update Resource "data-and-databases-data-ethics-resource-type/index"

Author: emilykateemilykate

content/posts/data-and-databases-data-ethics-resource-type/index.mdx

@@ -89,8 +89,6 @@ Categorisation ethics can be important even if the subjects of categorisation ar
 
 Ethical issues with how our information is handled in this way are linked to some practical data issues, but are not quite the same as them. Data can be sufficiently accurate for a project’s broadacademic aims but still be unethically framed in how it is presented in the dataset or in result write￾ups. Ethical issues may lie at a tangent to the core of the study: one might correctly observe a pattern in properly collected data, but whilst using outdated or harmful terms for how some of the data are framed, by failing to take into account social and political sensitivities over people and places that are involved. Whilst the problems of categorisation ethics are therefore closely linked to research design and rigorous analysis, they need separate consideration.
 
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 ## Data processing ethics
 
 The ethics of data processing and analysis are closely linked to those of categorisation and structure. 
@@ -107,7 +105,7 @@ These sorts of problems can be even worse when such technology is used in areas
 
 Even outside the world of artificial intelligence and advanced predictive technology, simpler analyses can equally cause problems if not thought through properly. For example, in textual analyses, a word frequency analysis across a group of publications may need issues of representation taking into account. Imagine a situation where in a group of written news outlets, an academic wanted to see how prevalent a particular topic was. If some of the news outlets cater to a particular ethnic group or region they might use a particular dialect or phrasings not used in a more standard version of the language. If not accounted for, this could lead to an analyst failing to pick up their coverage of the topic or even wrongly concluding that outlets in that region were disinterested in it. Taking into account the diversity of people and situations from which your data are gathered is vital to analysing it not only properly, but also ethically.
 
-As with the previous section, these problems are partly issues of doing rigorous academic work: badly trained AI or badly chosen analysis methods will come out with poorly framed or inaccurateanalytical results. They are also nonetheless specifically ethical concerns as well, and even if issues of this sort do not invalidate a study’s overall findings they could cause harm. It is therefore worth specifically reviewing your analysis plans along ethical guidelines and considering its impact on a range of groups and identities, separately from your considerations of the overall data gathering process and how it links to your research question.
+These problems are partly issues of doing rigorous academic work: badly trained AI or badly chosen analysis methods will come out with poorly framed or inaccurate analytical results. They are also nonetheless specifically ethical concerns as well, and even if issues of this sort do not invalidate a study’s overall findings they could cause harm. It is therefore worth specifically reviewing your analysis plans along ethical guidelines and considering its impact on a range of groups and identities, separately from your considerations of the overall data gathering process and how it links to your research question.
 
 ## Conclusion