One of the main institutions of a participatory economy is that jobs are balanced for desirability and empowerment. That is, the collection of tasks that a person does in their work are comparably desirable and comparably empowering to the collection of tasks that every one does in their work.
I would like to explore some details how this could be generalized as a theory, and offer one specific recommendation for how to proceed.
Some years ago, to prepare for the debate I had with David Schweickart, I did some research into the small number of real-life examples of balancing jobs. Both South End Press (according to Lydia Sargent) and The NewStandard (according to Jessica Azulay) had similar approaches to balance jobs at both workplaces: Aggregate all the tasks within a small number of categories (three or four), and then ensuring that everyone did a comparable number of tasks among all categories.
Michael Albert, in his book Parecon: Life After Capitalism mentions one example where tasks are given an empowerment rating by number which could serve as a basis for a general approach for balancing jobs:
We can then imagine someone giving each task a rank of 1 to 20, with higher being more empowering and lower being more deadening and stultifying. So in this experiment we have hundreds or perhaps even thousands of stripped-down tasks from which we create actual jobs.
The thinking is that given these rankings, it’s easy — or at least it’s feasible — to create balanced jobs. Take the average of the ratings. It certainly is feasible, but I believe there’s an easier way to approach this:
First, make a list of all of the tasks to be rated. As an example, let’s image a workplace with just three tasks:
Second, arrange the tasks in order from least to greatest for the desired ranking, assign the middle task in the order a ranking of zero:
Task A – score of ?
Task B – score of 0
Task C – score of ?
Third, assign the tasks with a lesser ranking a score with a negative number, and those with a greater ranking a score with a positive number:
Task A – score of -1
Task B – score of 0
Task C – score of 1
Now you can balance jobs simply by ensuring that the sum of hours spent on each tasks sums to zero. If there’s an imbalance, you immediately know in which direction to correct: If your job is too highly rated (that is, it has a cumulative score greater than zero), add the necessary number of tasks with a negative rating until you achieve
a sum of zero. Likewise, if your job has a rating too low (with a cumulative score less than zero), add the necessary number of tasks with a positive rating until you achieve a sum of zero. Repeat the process for each metric.
 In Michael Albert’s recent writings on balancing jobs, he appears to dispense with considering balancing jobs for desirability, focusing solely on empowerment. This would be at invariance to the original articulation of balancing jobs, and that which Robin Hahnel has consistently written about — that jobs are to be balanced for both desirability and empowerment. Robin Hahnel has even gone proposed to go further: in chapter 10 of the book Democratic Economic Planning, Robin and chapter co-authors Peter Bohmer and Savvina Chowdhury propose a third balancing criterion, that of caring labor, in order to make a participatory economy more equitable along gender roles which had an imbalance of caring labor. The proposal outlined here can be used to help balance tasks in a job complex along these and any number of other balancing metrics.