Multivariate analyses tell us which employee, job and workplace characteristics are 'really' associated with unreasonable treatment but, for many purposes, we simply need to know where the most troubled workers can be found. Where would a trade union look for unreasonable treatment amongst large concentrations of its members? In which employment sectors should a government agency, or a professional body like the CIPD, concentrate its efforts to try to reduce ill-treatment in order to get value for money? Such interventions do not have to rely on sophisticated, multivariate analyses to know where to start. Bivariate analyses, which tell us who is more likely to experience unreasonable treatment for one variable at a time, can help with this.

For example, bivariate analysis shows that the non-UK born and non-Christians were less likely to experience unreasonable treatment. This is only what we would expect – when we know how much more likely it is that white employees will experience unreasonable treatment than Asian employees – but it does allow us to conclude that we shall be less likely to find troubled employees amongst those who we might have imagined would be vulnerable because they are migrants from outside United Kingdom. Bivariate analysis also suggested that, contrary to some of the things said in Chapter 1, if we want to find workers who have been unreasonably treated we had better ask men rather than women. While this may 'really' be because women earn less than men and are less likely to have managerial responsibilities, the fact remains that women are less likely to experience unreasonable treatment than men. In addition, bivariate analysis showed unreasonable treatment was more likely in workplaces with lower proportions of women. While this was not a very strong relationship, these may, once more, be the workplaces where we would expect to find more people with managerial responsibilities and/or higher incomes.

The conclusion that unreasonable treatment was more likely amongst male employees adds to the emerging picture of unreasonable treatment as an affliction of the comparatively privileged rather than the most vulnerable sections of the workforce. As a mild corrective to this, bivariate analysis also showed unreasonable treatment to be higher amongst recent employees, and this was probably because younger workers were a little more likely to experience it. Recent employees may be new entrants to the labour market – and are therefore more likely to be younger – and younger people change jobs more often anyway. Employers may well find this useful knowledge to consider when managing new recruits.

Bivariate analysis of job characteristics revealed that unreasonable treatment was more likely amongst full-time workers and those in associate professional, professional and technical jobs. This perhaps reflects the multivariate results for age, income and managerial duties. Similar factors may also explain why bivariate analysis showed that union members were more likely to report unreasonable treatment. As we have implied before, trade unions and others who want to target large numbers who experience unreasonable treatment should concentrate on core rather than peripheral workers: full-timers in fairly good jobs who are more likely to be union members already.

If the section of the population most affected by unreasonable treatment is the aspirant middle class, it is highly unlikely that the typical workplace where unreasonable treatment goes on will be a private sector sweatshop with no human resource function and no union representation, and a low-paid and low-skilled workforce. It is therefore no surprise that bivariate analyses suggested that, if we want to find troubled workers, we ought to go to small-to-medium (50–249) workplaces rather than to workplaces which are any bigger or smaller. We also ought to bear in mind that at least 50 per cent of these workplaces were themselves part of larger organisations. Unfair treatment actually became more common as size of the organisation increased. Nevertheless, it remained the case that unreasonable treatment was more likely in highly visible organisations with human resource functions, union recognition and highly skilled and well-paid workforces.

There is no odour of the backstreet about unfair treatment. We find it, in fact, in modernity's shop window. Bivariate analyses showed that industries that have the largest proportions of workers experiencing unreasonable treatment were health and social work, public administration and defence, the utilities and financial intermediation. While this may really be because these sectors had more troubled workplaces, as indicated by higher responses to the FARE questions, there could be other factors at play.8 Some of these industries may have been more likely to employ disabled people, for example. Others may have been more likely to employ young people, or white people, or to pay higher wages.

Bivariate analyses showed that unfair treatment was more likely to be found where employees said they did not decide how much work they did. It seems likely this was because deciding how much work one did was very closely allied to one or more of the 'real' factors at play like organisational change, the intensity of work or the FARE questions. It is still the case, however, that finding employees with little autonomy will be a practical short cut to finding trouble at work.

Finally, it is worth saying a little about our bivariate analyses of troublemakers. We would expect them to have some of the same characteristics as troubled workers, not least because we would expect them to work in the same places. By and large, this is what we found: troublemakers were more likely to have managerial duties, be full-timers, work in associate professional and technical jobs, have super-intense work, experience organisational change and did not think their organisation cared for individuals or their principles. We also found, however, that a detailed industry breakdown showed troublemakers were spread across several industries.

The utilities and public administration were both more likely to have troublemakers, but the big concentrations were in construction and financial intermediation. These analyses used small numbers but the result for construction is intriguing. It might suggest, for example, that the managerial structure of some organisations is such that the task of re-creating a troubled workplace is quite a specialised one. In other words, that structure might only require that a senior manager, perhaps even an executive, should make a decision which results in unreasonable treatment meted out for many people. Thus one senior NHS manager can make sure dozens of people think they have an unreasonable workload, whereas, however much they want to, or have to, do it, the foreman on the building site can only make sure the workload of a small team is so affected.

This last point illustrates once more the key point we are trying to make in this chapter and, indeed, in this part of the book. For many people, and for a great deal of the time, trouble at work is not about bullies and victims or the stress endured by individual employees (Walker and Fincham 2011). It is about troubled workplaces and the sociological factors which contribute to them. So far we have isolated quite a few of these factors – age, disability, ethnicity, income, intense work, managerial responsibilities, organisational change, region and fairness and respect. It is now time to move on to incivility and disrespect, to see if the same factors carry over to a different kind of ill-treatment in the workplace.

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