While it is impossible to eliminate spin, we can take steps to minimize its likelihood.
The reason spin is inevitable is that people (being what they are) will always try to game the system. Personal preferences, power games, cultural styles and even technology literacy all get in the way of the end goal - pure transparency.
In addition, there is no getting away from the human bias on how pure data is presented. So the data itself is always suspect:
- Someone has to put the data into a format so that people can use it. That container is going to influence the way the data is perceived.
- "History is written by the winners." That's because there is no such thing as objective history, only the perspective of one party or another.
- Any phenomenon can be observed completely differently depending on whether you are looking through a historical, sociological, biological, religious, Western/Eastern, economic etc. lens.
- Relying on science is not an escape. Academics have a field day taking apart the methodology used to provide data. The fact that methodology is so easily manipulated is why I don't trust quantitative studies AT ALL unless they are cross-correlated with qualitative work.
So is truth possible? Because if it is NOT possible then spin is inevitable as part of any attempt to communicate. Which is why I say:
If data is inevitably presented in a biased way, narrative will always be worse.
Narrative itself entraps us in spin.
How then can we talk about anything? Perhaps conversation itself is a waste of time, because it's all biased.
No - we can instead put biases in conversation with each other.
Methodologically, this involves a balanced approach to data - quantitative and qualitative.
Communication-wise, this involves interaction - or social media.
The concept of "big data" is that we draw from the well of ALL available numbers, all available data, all available studies - and look for overarching trends.
But you can't get to "big data" unless you have data sets to begin with.
Data sets can be drawn from narrative (e.g. content analysis of what organizations say about their programs in their annual reports), from survey results (customer feedback on performance), to qualitative data (interviews, focus groups where questions are standardized), ethnography (journal notes), and even data collected without human intervention - such as computerized collection of information like call wait times.
What I am arguing is:
We need more data, not less.
The taxpayer owns the data.
We should make it available raw.
*As always all opinions are my own.