Quality Assurance for High Text Volumes
Is quality assurance for large volumes of text a mission impossible? Of course, there are now various tools that assess quality according to certain criteria. But honestly, are your texts really good in the end, i.e. do they work? That's what really matters, isn't it? ?
The reasons are obvious: simply pointing out symptoms of a lack of quality does not cure the text, and at the same time a good 'readability score' does not mean that the text fulfils its purpose. Speaking of the purpose of the text, it usually gets lost somewhere along the way... Pity, because what is more important than fulfilling a purpose??
So what now? What can we do??
The answer is to think differently. Quality means thinking in processes. ???
Then it will also work with large amounts of text - that's a promise. Because if you think about planning (goal, requirements, briefing, data, ...), production (production method, text creation, review loops, ...) and post-production (publishing, measuring, optimizing), you can link these steps together and automate them. For example, all the necessary information flows into a briefing, a prompt, or a set of rules, and is later analyzed in a quality control process, while performance metrics are linked to quality.?
But my colleague Adela explains this in much more detail, more scientifically and with more background. In her blog post, she addresses the topic of quality with a lot of text.?
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