Today is an early stage #WorkingOutLoud post, as i work with Emilie to analyse and interpret the initial data from the Landscape of Trust research. I’m using this post to develop some ideas to include within the first Research Report, that will be available later this month. If you haven’t been following it, here is a summary: The ‘Landscape of Trust’ project is research into ‘what trust means’, and ‘how it flows’ through organisations. It’s an open data project, global, large scale, gathering stories (narrative accounts). Today (for the first time) i’m trying to write some narrative around this, an early summary of the ‘emotional tone of the narratives’.
When people take part in the research, they share stories: ‘what does trust mean to you’, ‘how does trust fail’, and so on. There’s an approach you can use to categorise these stories, called critical discourse analysis, whereby you create ‘buckets’, and put stories into each bucket. For example, we have one ‘bucket’ called ‘ANGER’. If people use the words ‘betrayed’, ‘broke’, or ‘closed’, we put the story in the ‘anger’ bucket. In fact, you first analyse all the stories, take out all the descriptive words, and create a whole series of buckets. These are the buckets shown here, and a few examples of the words that sit within them:
Joy: ‘heart’, ‘believer’, ‘successful’
Sadness: ‘alone’, ‘left’, ‘abandoned’
Anger: ‘betrayed’, ‘broke’, ‘closed’
Fear: ‘struggle’, ‘scared’, ‘unknown’
Disgust: ‘unacceptable’, ‘failure’, ‘loathe’
I hope that makes sense… i’m not the best researcher in the world… but luckily i have Emilie to help out here. Everyone needs an Emilie. If you have questions, please just ask, because i need to learn to share these stories effectively.
Now we get to the hard part: what does this mean. At this point, i need to be clear: i am sharing opinion. We are not yet at a suitable size of study to produce statistically significant results, and even when we are, data are subject to various interpretations, and i can only offer one. So this is my best read of what we are seeing: as with any of my work, feel free to re-sketch it and draw your own conclusions. Eventually the whole data set will be open and free for you to do just that.
There are two key indicators i’m interested in here: ‘ANGER’ and ‘JOY’. Anger, because of the clear and strong gender separation, and Joy, because it’s the strongest, and very equal, effect, across genders.
We could read Anger in one of two ways. One reason for this result may be a skew in the participants themselves. Currently more women have responded than men, and whilst the ratio does not match this difference, it may contribute to it. Or, alternatively, it may be that women and men use different words to describe trust! Another possibility is that we have introduced a bias through our coding, although the choice of which words go in which bucket can be calibrated, at least to some degree, but using pre-determined sets, or getting multiple people to code.
This is not the first strong gender effect we have seen, but equally, other gender based effects have ironed out or reversed as the sample size increased, so take your pick of reasons at this stage.
The second effect i’m most interested in is Joy. How can we read this: is there a tendency towards optimism? Or is part of the process of rationalising failure in trust a tendency to look for positives, to prove, if only to ourselves, that we have learnt, that we are better for it?
Aside from these two key factors, also of note is that the language of ‘Disgust’, and ‘Fear’, is used very little. Why? Well, it may simply be the sample size, or it may be that people who take part in studies into trust are optimistic or prone to rationalise the behaviour of others… or perhaps there is simply a clear separation, that we tend not to associate trust with these two factors. Intuitively that feels wrong, but that’s the point of the research: to calibrate intuition with evidence.
One other notable point: for both genders, ‘trust’ is described in quite analytical terms: very few participants use confident language. That may correlate to a result from the prototype study last year, where only 6% of individual had ever had an explicit conversation about ‘trust’ at work. The very fact that we are giving people an opportunity to reflect may be triggering this analytic reflection.
I’ll close with this, and, again, it’s an opinion. My sense is that we will not uncover ‘an answer’ to trust. Because trust is multi layered, complex, contextual, adaptive, fluid. Our success will lie in creating a matrix, a framework through which to consider trust: perhaps a guided series of conversations or spaces, through which we can build a shared understanding of our differences.