Beyond Unemployment Insurance in the Face of Structural Job Loss

“The long memory is the most radical idea in America.”
 Utah Phillips, as recalled by Amy Goodman

I was reminded of Utah Phillips’ observation as I sat down to write this essay on how we approach public policy for dealing with unemployment during a time of mass unemployment. I intended to start off the essay by recalling Thomas P. Hoerr’s 1988 book , which bore the enticing title, And the Wolf Finally Came. It’s a book about several decades of ups and downs of steel making in Pittsburgh. The author recounts how Pittsburghers had over the years grown accustomed to those ups and downs, until one year, as one of Hoerr’s sources told the author, “the wolf finally came”; that is, those troublesome ups and downs got replaced by very much more troublesome downs and downs. But that would show some memory, and I sure wouldn’t want to be labeled a “radical”—heck, I am not now, nor have I ever been, at the Academy Awards.

Hoerr’s recounting provides a pointed reminder of how unprepared public policy makers can be for—to borrow a word from Jarrod Diamond—Collapse!; and so, how unprepared they can be for Transformation! and for Learning! I should add that Mancur Olson’s “logic of collective action” predicts foot-dragging by groups who disproportionately benefit from “keepin’ on keepin’ on” with established technology instead of adopting—and adapting—to new technology, the adoption of which would usually entail rearranging relations of power; see Olson’s The Logic of Collective Action; also, chapters 2 and 3 of his The Rise and Decline of Nations, which summarize the first book.

The question that links all these points is, what if the current economic “downturn” is really Hoerr’s wolf finally coming… for the whole US economy? If that’s the case, then unemployment compensation, the primary public policy tool, becomes obsolete, immediately. That’s because unemployment compensation was conceived as a temporary solution to a temporary problem, getting people through the down part of one cycle to the up part of the next cycle; not as a long-term solution to a long-term structural problem. (Capitalists often use war for that.) Not coincidentally, such Keynesian-inspired—certainly not justice-seeking—payments facilitate the capitalist practice of accounting for labor as a variable cost, always to be minimized, rather than as a fixed or resource cost, to be sustained. The real beneficiaries of this practice are capitalists… and Hoerr’s wolf, which feasts on long-term, structural problems.

What to do? No country can keep paying people to not work for what could easily become an oxymoronic “permanent interim” period. Think of buggy-whip makers, after the (“horseless carriage”) wolf finally came to places where horse-drawn carriages and related products had been made.

The only viable public policy option is Change! And the only potentially workable approach to such policy is Transformation-through-Learning! One workable approach to that would entail changing over to the sort of future-responsive social learning program envisioned by Donald N. Michael in his seminal book, On Learning to Plan—and Planning to Learn (JosseyBass, 1973); later reissued as a second edition, with the leading “On” omitted (Miles River Press, 1997).

But learning is never easy; even acknowledging that learning “just might possibly maybe, sort of, somewhat… well… necessary” can seem to be, and can in fact be, frightening—personally, professionally, financially, and other ways as well. Dreams dissolve, along with institutional premises upon which they had been premised. Some people get blamed, and no one knows when more constructive activities have finally supplanted the so-called “blame game”.

Those sufficiently courageous to acknowledge that learning is needed must then deal with the even greater difficulty entailed in actually doing the learning. And that includes exposing oneself to not-yet familiar evaluation criteria applied by not-yet familiar people in not-yet familiar institutional settings, with outcomes extending from something seen as “success” to something seen as “failure”, and including unsettling outcomes that a person had previously felt insulated from—all demanding even more courage.

But, we must find the courage to learn if we are to fend off Hoerr’s wolf, even if we must risk failing to do so. That’s because we certainly can’t do any better in our Transformation-through-Learning! than we do in our learning itself. Hoerr’s wolf sees right through grade inflation, ego inflation, expensive marketing campaigns, and other forms of individual and institutional self-validation.

How can we attempt to do this? By way of example, let me suggest a way that the US government might have leveraged General Motors—long perceived as unwilling and/or unable to learn—into learning. (I mean, GM shouldn’t have been allowed to expect the government to give it all the billions it had requested, with no strings attached—should it?) The government should have held hearings that would have focused not so much on how GM’s new plan would have “restructured” and “cuts costs”.

Instead, the hearings should have focused on whether, how, and how well GM’s new plan incorporates learning from their most recent, wretchedly mistaken plans. Somehow, some of GM’s top managers came up with those wretchedly mistaken plans, and some other group or even groups signed-off on adopting them. GM officials must somehow persuade representatives of taxpayers that they have searched out and identified that “somehow” and learned how to avoid it (and how to recognize and avoid situations like it) in developing their current plan for which they would like to borrow a few billion bucks.

Here are some of the questions I’d ask them to discuss.

  1. Starting two plans ago, with the plan on which the most recent, failed plan was based, how was the set of candidate goals developed? How were goals selected from those candidate goals? How were goals prioritized? What variables were used? How was disagreement regarding goals selected and/or how those selected goals were prioritized handled? How often did the CEO end up on the losing side, and what portion of total dollars decided about did those “losses” represent?
  2. How had GM gone about projecting and evaluating those outcomes? How had GM distinguished between contingencies they had encountered? How had GM gone about distinguishing between [2a] unanticipatable contingencies and [2b] anticipatable contingencies, incompetently handled?
  3. How did each executive interact with his or her subordinates, and how would each executive characterize his or her subordinates’ interactions with their subordinates – down to and including the people who actually make automobiles for GM? How were the implementation and operation of these plans considered in development of these people, and so, in output projections and evaluations? Are employees still wearing “Golden Handcuffs” to reduce risk of losing their jobs? What provision, if any, did the executives make for feedback – whether favorable or unfavorable – and for incorporating learning based upon it into the plan?
  4. How did GM decide that their plan was “done”?
  5. [Responses to questions 1-4 would provide a benchmark for further questioning aimed at understanding GM’s approach to learning to change.]
  6. Regarding the then-current failed plan, how did the process through which the follo-on plan was generated differ from what GM had reported about the immediately previous plan? Which elements changed; which did not? How were such distinctions reached?
  7. How is the change from the most recent past plan to the one then being submitted different from the change from the first of the plans discussed above to the most recent past plan?
  8. Finally, to lend some solidity to all these more obscure procedural matters, approximately how would GM spend each marginal $1/2 billion? What specfic substantive and financial benefits would each marginal $1/2 billion expenditure contribute to the success of your plan.

letcherThis approach would afford at least a glimpse into GM’s decision-making process, including how and even whether GM is able, willing and inclined to learn as well as how well GM actually goes about learning and building what it does learn into decisions it takes and actions it undertakes. Hopefully, but far from certainly, such a glimpse would help to inform taxpayers’ representatives of GM’s prospects—which is to say, whether loaning the next GM the money would turn the company around, or merely give Hoerr’s wolf a really big meal.

Robert A. Letcher, PhD

Robert A. Letcher, Ph.D describes himself as “an academic with a disability instead of a portfolio, a writer, and a Qigong practitioner who tries to help people learn”.

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