Policy optics are concepts, analogies, methods and counternarratives used to recast issues currently defined as intractable. Recastings, if they work, remake (redescribe, recalibrate, reframe, revise, reorient) an issue more tractably. I seek to explain and describe how this is done in When Complex Is As Simple As It Gets (http://When Complex is as Simple as it Gets: Guide for Recasting Policy and Management in the Anthropocene)

But policy optics also function as prompts when they pose new but important questions and as probes when they reach for answers to So what?. This is an achievement even if both redefined questions and answers fall short of full-blown recasting. Below are 8 short examples of prompts and probes, in no order of priority, culled from the blog. Though some touch on topics in the Guide, all are new material and shortened from the original entries (where the references can be found).

1. First: differentiate equality
2. Apocalypse and tax havens
3. There is no workaround for improvisation by central banks in the next fiinancial crisis
4. “Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.”
5. Doing more in the climate emergency
6. Doing less in predicting the future
7. The scariest term ever produced by business schools: designing leadership
8. But it is in my back-yard!

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1. First: differentiate equality

Much of the debate over equality has been and remains at the macro-principle node. We all have equal rights; we all should have equal opportunities. Yet from the very beginning, exceptions have been in the form of specific contingency scenarios read off the macro, e.g., people are in principle equal but people are not born with the same and equal potentials. Contingency scenarios qualifying the reading of macro-principles litter debates over equality.

As the genetics we are born with are of course not everything, we also find vast differences in human-by-human particularities. Equal at the macro level, the most obvious fact at the micro-level is how unequal each person is in so many ways. Macro-principle, principle-based contingency scenarios and micro-experience are, however, not the only nodes around which equality debates organize.

The gap between macro-principle on paper and system behavior in practice is also everywhere evident. Systemwide pattern recognition, our fourth node, is populated by all manner of trends and statistics that show, e.g., just how unequal income, wealth and consumption distributions are within and across countries. Indeed, the difference between equality as professed and equality as realized is benchmarked by this gap between macro-principle and the recognition of systemwide patterns.

So what?

Put plainly, the macro-node in equality debates formalizes as principle what others cannot help but seek to informalize more through exceptions and contingency scenarios. The micro-node informalizes what others cannot help but seek to more formalize when they talk about systemwide patterns emerging across different cases. Equality, in this way, can’t help but be a messy project.

Nothing stops privileging one over another, or some over others, even though all four nodes are interconnected. There is, however, a world of difference between privileging one node from the get-go versus answering the question, “What do we do here and now with respect to this case of (in)equality”. The latter requires assessing all four nodes with their conflicts and examples.

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2. Apocalypse and tax havens

I

Novels and scenarios about post-apocalypse are dystopian when it comes to the climate emergency: Nothing will be as it was before. But it’s that “nothing will be as it was” that bothers me.

An example, and one to which the reader can relate: tax havens. Once you have an inkling of what to look for, the numbers loom massive.

In one year alone (2016), multinational corporations (MNCs) were estimated to have shifted USD 1 trillion of profits to tax havens, with an estimated USD 200-300 billion in lost tax revenue worldwide. (The Cayman Islands, Luxembourg, Bermuda, Hong Kong and the Netherlands are among the most important tax havens.) Another study estimates multinational enterprises shift close to 40% of their profits to tax havens globally. As for regions, the main European banks are reckoned to have booked EUR 20 billion (close to 15% of their total profits) in tax havens. In Germany, by way of one country, MNCs there are said to have shifted corporate profits of some EUR 19 billion to tax havens, with an estimated tax revenue loss of roughly EUR 5.7 billion.

Now, post-apocalypse: The Cayman Islands, Bermuda, Hong Kong and the Netherlands? Under water. MNCs? They should be so lucky! Tax havens and forgone tax revenues? After the apocalypse, what taxes?

In other words, the bad of tax havens, pre-apocalypse, is made moot post-apocalypse.

So what?

Well, first off, why ever then are we spending time and resources on reducing the use of tax havens when all our energies—all our political will—should be directed to averting the climate-induced apocalypse? From this perspective, today’s tax havens are visibly part of opportunity costs of deadly climate inaction. Reducing tax havens is worse than meaningless unless the generated revenues are directed to mitigating the impacts of climate change—and even then the prospect of “too little too late” looms.

Or is it too little too late in quite another sense? For surely part of being in the apocalypse means we have to manage global climate change far better everywhere than we (can) manage tax havens here or there, and now. If so, we are on the losing end either way: managing (or not) tax havens won’t get us to the climate change mitigation needed. . .

Unless of course, we imagine that getting rid of these tax sinkholes for the rich and already-undeserving—the enemy of both populist and cosmopolitan citizenship—are among the few things that are truly urgent, like the climate emergency.

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3. There is no workaround for improvisation by central banks in the next fiinancial crisis

I

Undertake a thought experiment. Assume we are actively in the lead-up to another financial meltdown and fund managers are making the same or similar points as in the last one. For example: We don’t know where the risks are. Ask now: What would be success or effectiveness for these managers under the current conditions?

One answer I highlight is that of a senior emergency manager who recently told us: “Success in every disaster is that you didn’t have to get improvisational immediately. You can rely on prior relationships and set up a framework for improvisation and creativity.”

More formally and back to our thought experiment, management success in this lead-up to the next financial meltdown is no longer one of preventing that meltdown from happening. It’s better to think that this lead-up is its own disaster and now ask: Where is effective emergency response going on presently or should be going on?

II

So what? While no detailed failure scenarios are possible here, the thought experiment can be extended in illustrative ways. Stay with the US setting. For example, assume all or several of 12 US Federal Reserve Districts and their respective Banks officially activate as Emergency Operations Center under the Incident Command System. Each Bank retains its mandates for price stability, maximum employment and interest rate regulation within its specific, widely varying regions. What then could/would/should each Bank-EOC do differently in the next two months?

Which is by way of answer: When it comes to immediate response to this disaster called the lead-up to the next financial meltdown, there is and can be no workaround for improvisation.

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4. “Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.”

More than a year ago a joint statement was issued by the Center for AI Safety. It was the one sentence quoted above. Famously, it was signed by more than 350 AI experts and public figures.

Now, of course, we cannot dismiss the actual and potential harms of artificial intelligence.

But–and here’s the answer to the “So what” question, these 350 people must be among the last people on Earth you’d turn to for pandemic and nuclear war scenarios of sufficient granularity against which to appraise their AI crisis scenarios.

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5. Doing more in the climate emergency

I

I attended an informative conference on sea-level rise, storm surges and flooding in the greater San Francisco Bay Area, now and projected into the near decades. I was told:

• that Bay Area would need some 477 million cubic yards of sediment–the vast majority of which can’t be sourced locally–to restore area wetlands and mudflats;
• It would require an estimated US$110 billion dollars locally to adapt to higher sea levels by 2050, this being based on existing plans in place or used as placeholders for entities that have yet to plan; and
• To expect much more sea level rise locally because of the newly accelerated melting of the ice cap melting in Antarctica and Greenland.

Millions of cubic yards equivalent to over 420 Salesforce Tower high-rises? Some $110 billion which has no possibility whatsoever of being funded, locally let alone regionally? How are these and the other unprecedented high requirements to be met?

II

But there is a major problem with these estimates of losses (economic, physical, lives, and more) incurred if we don’t take action now, right now. It’s been my experience that none of these estimated losses take into account the other losses prevented from occurring by infrastructure operators and emergency managers who avoid systemwide and regional system failures from happening that would have happened had they not intervened beforehand, sometimes at the last moment.

So what?

Why are these uncalculated billions and billions of saved dollars important when it comes to responding to sea level rise, increased storm surges, more inland flooding, rising groundwater levels and other sequelae?

Because it from this pool of real-time talent and skills and practices that society will be drawing for operationally redesigning the inevitable shortfalls in new technologies, macro-plans and regulations for climate restoration and recovery.

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6. Doing less in predicting the future

So what if we’re lousy in predicting the future? We are so used to the idea that predicting the future is more or less about accuracy that we forget how murky and unclear the present is. To paraphrase Turgot, the French Enlightenment philosopher and statesman, we have enough trouble predicting the present, let alone the future. Because the present is not one-way only by way of interpretation, why expect anything less for the future?

Again: So what?

This means that the microeconomic concepts of opportunity costs, tradeoffs and priorities, along with price as a coordinating mechanism make sense–if they make sense–only now or in the very short term, when the resource to be allocated and alternatives forgone are their clearest. Without opportunity costs, notions of stable trade-offs and prices go out the window.

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7. The scariest term ever produced by business schools: designing leadership

Take even a cursory glance at the track record of advisers to their leaders:

• Plato and Dionysius II;
• Aristotle and Alexander the Great;
• Seneca and Nero;
• Ibn Rushd (Averroes) and Caliph Abu Yaqub Yusuf;
• Petrarch and Emperor Charles IV;
• Montaigne and Henri IV;
• Descartes and Sweden’s Queen Christina;
• Leibnitz and the Dukes of Hanover;
• Voltaire and Frederick the Great;
• Diderot and Catherine the Great; and
• In case you want to add to the list, Adam Smith and the Duke of Buccleuch or Goethe and Prince Carl August, and so on through the centuries. . .
• Or if you really want to cringe, just consider André Gide recommending against publishing Marcel Proust, Edward Garnett against publishing James Joyce, and T.S. Eliot against publishing George Orwell. . . .

I mean, get real: If these guys didn’t advise effectively, who the hell are we to think we can do better for the leaders of the day? (And, puhleeese, don’t throw up Kissinger and Nixon as the working template!)

So what?

Two things. It’s hard to imagine two words scarier in the English language than “designing leadership.” Second, we should take to heart the extensions of, “It was beyond our mental capabilities to predict Bob Dylan winning the Nobel in 2016.”

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8. But it is in my back-yard!

I

They believe that climate change is actually happening but don’t want those wind-farms off their coastline. Those driving electric cars are opposed by those demanding no more cars, period. Those who demand more renewable energy here are among those opposing construction of new transmission lines from renewables there.

The commonplace is to insist tradeoffs are involved. But tradeoffs aren’t the only, or even priority, starting point.

II

How so? Start with an observation in an online New York Times,

While China is the world’s biggest adopter of clean energy, it also remains the world’s biggest user of fossil fuels, particularly coal. “We have to hold these two things, which can seem contradictory, in our heads at the same time,” [another Times correspondent] said. “China is pulling the world in two directions.”

This may not be a contradiction so much as a transition.

German Lopez in The New York Time’s online Morning, August 14 2023

That is: What if those NIMBYisms are not contradictions so much as part of transitions underway? What if the oppositions aren’t stalemates but are already leading to something different?

III

One such complex transition underway is the transfer of renewable energy between and across different electricity grids in the US.

As has been reported, there is a pressing need for new transmission lines. But that new construction would add to a base that already involves inter-regional electricity transmission, including for clean energy. True, how much of that transitioning is going on is hard to document. True, the regional grids are fragmented and true, more renewable energy interconnections are needed.

IV

So what?

Take a case where city residents objecting to wind-farms off the coastline are served by a grid not inter-regionally connected to clean energy sources. One interconnectivity solution to this Nimbyism would be to hike up the electricity rates of city residents: not just because they are forgoing clean energy but also because their rates for the interconnected water, cellphone and transportation subsidize their choice.

Transitioning to clean energy in my back-yard is already in the front-yard of inter-regional energy infrastructures.

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The massive backlog of deferred maintenance for public housing in the United States demands a comprehensive, holistic solution that brings every unit in the country up to the highest health and environmental standards: A Green New Deal for Public Housing. This plan would deliver healthy green upgrades and deep-energy retrofits of the nation’s public housing stock to massively increase residents’ health and quality of life, finally remedy the long backlog of repairs in public housing, and eliminate all carbon pollution from public housing buildings, while creating badly needed, high quality jobs in the green economy for people in public housing communities.

(My bold. Accessed online at https://www.climateandcommunity.org/gnd-for-public-housing-2024#:~:text=The%20massive%20backlog%20of%20deferred,New%20Deal%20for%20Public%20Housing.)

So what?

I understand that we don’t want things to be false, we want things to be true, but then there’s the leap from authenticity to the idea of purity, and therefore, what is not authentic or pure is somehow corrupt, and that’s the danger zone.

Jhumpa Lahiri, essayist and novelist

(Accessed online at https://www.theguardian.com/books/article/2024/may/29/our-obsession-with-origin-is-a-global-danger-says-jhumpa-lahiri-hay-festival#:~:text=%E2%80%9CI%20understand%20that%20we%20don,danger%20zone%2C%E2%80%9D%20she%20added.)

Ferality is a foundational concept in your research. It expresses ‘nonhuman beings engaged with human projects’ and ‘human infrastructures but outside human control.’ . . . Ferality also refers to the harmful impact of human infrastructures on the environment; notwithstanding simplifications, how do we understand what qualifies as either negative or positive from an environmental and non-anthropocentric perspective?

Feral stands beyond the conventional ‘domestic vs. wild’ dichotomy, which is still human-centric. Generally, people understand ‘feral’ as lying within the ‘wild’ category that has nothing to do with humans, whereas ‘domestic’ is completely human-controlled. Still, what ferality engages, as you said, is about being developed beyond human control. Understanding that the feral effects are undesigned is the key. . .That our infrastructural systems encourage and facilitate the emergence and spread of feral ecologies — in ways humans did not intend — is crucial to comprehending why they remain uncontrollable and resistant to human intervention. Ferality does not point only to the negative or harmful impact; ferality can be good, in a subjective sense. . . .

Instead, we’re pointing to these processes in which ferality is produced, and looking at what kinds of proliferations, species declines, and ecological ruptures result from the undesigned consequences of Imperial and industrial projects.

So what?

One precious thing about [our digital research publication] Feral Atlas is the way that images, art and poetry were woven into the analysis. I think of Feral Atlas as an intermedial analytic performance, and for me that’s a great strength. An intermedial approach to knowledge creation curates and orchestrates different forms of empirical description and expression, without forcing them into a homogenous narrative or form. . . .

From a personal point of view, I find there is great value in such methods; particularly in terms of a question that is never far from my mind these days, namely ‘How are we to live’? Before we started Feral Atlas, the terror of ecological danger often overwhelmed me to the point of intellectual and social paralysis. As a result of working on this project, alongside so many others who are similarly terrified, I find myself better able to get on with life, mobilised by being part of a broader creative, critical and transdisciplinary engaged community of open-eyed concern.

https://www.koozarch.com/interviews/on-ferality-patches-and-infrastructures

I

Consider the familiar two-by-two typology that produces known knowns, unknown knowns, known unknowns, and unknown unknowns. We may think all the bases are covered. Now throw in an apparently related term, but from a different field entirely, namely: the “unthought known” of Christopher Bollas, a concept as well-known in psychoanalysis. Mix two genres–Rumsfeld’s fourfold typology and Bollas’s psychoanalytic insight–and you realize the initial distinctions are more complicated.

Known-unknowns are said to be risks that we are aware of, but we don’t fully understand. For example, we may know that there is always a risk of a new competitor entering the market or political arena, but we don’t know how likely this is or what impact it would have on competition or politics. Unknown-knowns are said to be things you’re not aware of but do understand. For example, you know gender bias, but didn’t know it was actually happening in the competitive process of interest to you.

ii

The unthought known, however, is a kind of knowing that you have not thought about. It is unconscious and often associated with trauma, rendering the unthought known, “unconsciously compelling,” as Bollas puts it. For instance, you know you’re (un)safe without even having to think about it.

How so? Return again to competition and the economic literature on all manner of non-conscious herding behavior, bandwagon effects and market contagion under conditions of deep uncertainty and rapid imitation. Here economic meltdowns, burst financial bubbles and scapegoating give birth to new market rules and wraparound structures, safer for some but not for others.

These phenomena may seem like unknown knowns–we know herding behavior when we see it!–but one must wonder if they are understood psychoanalytically or mimetically as described and formulated.

Unthought knowns, I submit, remain highly policy-relevant, even if the concept doesn’t fit squarely in with known knowns, unknown unknowns, known unknowns, and unknown knowns.

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Sources.

–Christopher Bollas (2011). The Christopher Bollas Reader. Routledge: London and New York.

—https://mess-and-reliability.blog/2024/07/06/market-contagion-girardian-economics-and-its-recasting-of-financial-crises-updated/

I

A young researcher had just written up a case study of traditional irrigation in one of the districts that fell under the Government of Kenya’s Arid and Semi-Arid Lands (ASAL) Programme. (We’re in the early 1980s.) I remember reading his report and getting excited. Here was detailed information about really-existing irrigation practices and constraints sufficient to pinpoint opportunities for improvement. That was, until I turned to the conclusions: What was really needed was a country-wide land reform.

Huh? Where did that come from? Not from the details and findings in the report!

This was my introduction to pre-existing solutions in search of new problems they should “solve.” Only later did I realize I should have asked him, “What kind of land reform with respect to what and under what conditions at your research site?”

II

Someone asserts that this policy or approach holds broadly, and that triggers your asking:

• Under what conditions?
• With respect to what?
• As opposed to what?
• What is this a case of?
• What are you–and we–missing?

Under what conditions does what you’re saying actually hold? Risk or uncertainty with respect to what failure scenario? Settler colonialism as opposed to what? Just what is this you are talking about a case of? What are you and I missing that’s right in front us?

I

It shouldn’t be surprising that the more comprehensive a theory of materialist determinism, the easier to find the exceptions.

It is understandably more common then that the view of bureaucratic and authoritarian governments wielding infrastructural power for their own interests is contrasted to those empirical cases indicating quite otherwise. In these comparisons, the infrastructures are demonstrably weak, in need of great repair and maintenance, perform far less effectively than designed, planned or promised, require massive repurposing in light of the Energy Transition, and where the infrastructures’ real-time operators are barely managing or coping precisely because they don’t have the kind of control that many discussions attribute to “infrastructural power.”

Yes, critical infrastructures—even in their variably existing, heterogeneously performing conditions—still have major bearing on all those material factors taken to be important ranging from income and wealth inequalities and well-being to national and international versions of growth, prosperity and sustainability. But that impact is more differentiated and case-by-case than over-arching theories of materialist determinism allow. The former’s keywords and terms include: unpredictable, inadvertent, unintended, contingent, with many intervening variables.

II

For example, it’s routine to say that governments have allocative, distributive, regulatory and stabilization functions. In actual fact, infrastructures exercise a different and more variegated form of societal regulation by prioritizing systemwide reliability and safety as social values in real time. This matters for any understanding of “infrastructural power.”

Consider the commonplace that regulatory compliance is “the baseline for risk mitigation in infrastructures.” There is no reason to assume that compliance is the same baseline for, inter alios, the infrastructure’s eyes-and-ears staff on the ground; the infrastructure’s headquarters’ compliance staff responsible for monitoring industry practices for meeting government mandates; the senior officials in the infrastructure who see the need for more enterprise risk management; and, last but never least, the infrastructure’s reliability professionals—its real-time operations personnel, should they exist, and immediate support staff— in the middle of all this, especially in their role of surmounting any stickiness by way of official procedures and protocols undermining real-time system reliability and safety.

Stickiness? Noncompliance may be a regulatory error for the regulator of record; the same noncompliance may be an important option for ensuring system reliability when the task environment indicates the said regulation to be defective. Indeed for real-time operations, noncompliance is not an error, if following that regulation jeopardizes infrastructure reliability and safety now or in the next steps ahead. Indeed, the importance of time from discovery to correction of error reinforces a process of dispersed regulatory functions, where one of the regulatory functions of the infrastructure’s real-time operations is to catch and correct for error by the regulator of record under conditions of mandated reliability.

III

True, governments rely on infrastructures to meet their own functions and, yes, there is an overlap and dependency between both as the case of compliance illustrates. Few, however, think to ask, let alone study, how critical infrastructures—many of which are privately owned or managed in the US—independently and differentially affect society-wide risks, social values and societal regulation. It’s all well and good to stress there are other social values than reliability and safety. But it also useful to remind ourselves that much, if not most, of the world is characterized by unreliable and/or unsafe critical services—notably water and electricity—even where there are infrastructures of sorts providing the services.

So yes of course, operating these infrastructures, reliably or otherwise, create inequalities and exclusions. But wouldn’t you want to know before changing them the likely effects on systemwide reliability and safety of that change, however well-intended? (The chief lesson of Policy Analysis 101 is: The opposite of good are good intentions.) Even low-cost, more sustainable socio-technical systems will be reliable only up to that unpredictable failure ahead they can’t or haven’t prevent. They too will have to manage or cope because they too can’t control the Anthropocene when it comes to an infrastructure’s inputs, processes and outputs.

More, you needn’t be clairvoyant to realize that the Energy Transition–whether in its reformist or radical versions–means a host of second chances for critical infrastructures and their mandated provision of reliable services.

With or without Stop-Oil, infrastructures will remain central to energy provision and interconnectivity; with or without Sustainability, reliability and safety will be demanded across that interconnected provision. Technologies and system configurations will change, but even the keywords of radical versions of the Energy Transition—transformative, emancipatory—are redolent with the promise of second chances along the way.

What makes the second chances so important? For one thing the Climate Emergency portends all manner of illiquidity, not least of which are today’s infrastructures being tomorrow’s stranded assets. But “stranded” underscores the place-based character of the infrastructure. Stranded also implies the possibility of its other use(s), second chances in other words. One has to wonder if current Energy Transition scenarios are granular enough to take them seriously.

IV

Why is increased granularity of scenarios important? Critical infrastructures are themselves importantly differentiated. Some have centralized operation rooms or floors; others do not. Even those with an operations center vary majorly with respect to the reliability of their critical services. In particular, they may well be operating to different standards of reliability, from which follows they are managing for different risks and uncertainties.

For instance, it is true that nuclear explosions occur, dams are overtopped, and grids do separate and island, but these events are rare–rare because of their real-time management beyond the defects of technology and design–and when these events do happen they serve to reinforce a societal dread that they indeed are must-never-happen events. Real-time system operators seek to preclude must-never-happen events like loss of nuclear containment, cryptosporidium contamination of urban water supplies, or jumbo jets dropping from the sky because of that widespread societal dread.[1] (Which of course can change, and not just because of the Anthropocene).

In contrast, financial services have “should-never-happen events”—bank runs should be avoided and financial crises shouldn’t happen. The standard of operating reliability is not one of precluding financial crises from ever happening, but rather of treating these crises (1) as avoidable though not always, or (2) as inevitable (“busts are part of market capitalism”) or at least (3) compensable after the fact (as in the pre-2008 assurance that it’s better to clean up after a financial bubble bursts than trying to manage it beforehand).

So what? Well for one thing, not having highly reliable financial services based on must-never-happen events has major consequences for standards of economic stability and growth (also variously defined). At the macro level, there are two different standards of economic reliability: The retrospective standard holds the economy is performing reliably when there have been no major shocks or disruptions from then to now. The prospective standard holds the economy is reliable only until the next major shock.

Why does the difference matter? In practical terms, the economy is prospectively only as reliable as its critical infrastructures are reliable, right now when it matters for economic productivity (again, broadly writ). Indeed, if economy and productivity were equated only with recognizing and capitalizing on retrospective patterns and trends, economic policymakers and managers could never be reliable prospectively.

By way of example, a retrospective orientation to where we are today is to examine economic and financial patterns and trends since, say, 2008; a prospective standard would be to ensure that–at a minimum–the 2008 financial recovery could be replicated, if not bettered, for the next global financial crisis. The problem with the latter–do no worse in the financial services sector than what happened in the last (2008) crisis–is that benchmark would have to reflect a must-never-happen event going forward. What, though, are the chances it would be the first-ever must-never-happen event among all of that sectors’ should-never-happen ones?

V

Not only do these reliability standards differ, so too do the risk and uncertainties that follow from managing to the respective standards. The classic case is the one emergency within and across infrastructures infrequently discussed: suicide for fear of death.

What else can we do, senior executives and company boards tell themselves, when business is entirely on the line? In this emergency, we have to risk failure in order to succeed!

But what if the business is in a critical service sector? Here, when upper management seeks to implement risk-taking changes, they rely on real-time reliability professionals, who, when they take risks, only do so in order to reduce the chances of failure. To reliability-seeking professionals in critical infrastructures, the risk-taking activities of their upper management look like a form of suicide for fear of death.

This has become an all-too-common phenomenon. When professionals are compelled to reverse practices they know to be reliable, the results are deadly. Famously in the Challenger accident, engineers had been required up to the day of that flight to show why the shuttle could launch; on that day, the decision rule was reversed to one showing why launch couldn’t take place.

Once it was good bank practice to hold capital as a cushion against unexpected losses; capital security arrangements now mandate they hold capital against losses expected from their high-risk lending. Mortgage brokers traditionally made money on the performance and quality of mortgages they made; in the run-up to the 2008 financial crisis, their compensation changed to one based on the volume of loans originated but passed on.

Originally, the Deepwater Horizon rig had been drilling an exploration well; that status changed when on April 15 2010 BP applied to the U.S. Minerals Management Service (MMS) to convert the site to a production well. The MMS approved by the change. The explosion occurred five days later.

In brief, ample evidence exists that decision rule reversals that required professionals in high-stakes situations to turn inside out the way they managed for reliability have instead led to system failures: NASA was never the same; we are still trying (in 2024!) to get out of the 2008 financial mess and the Great Recession that followed; the MMS disappeared from the face of the earth.

“But, that’s a strawman,” you protest. “Of course, we wouldn’t deliberately push reliability professionals into unstudied conditions in critical support sectors, if we could avoid it.” Really? The oft-recommended approach, Be-Prepared-for-All-Hazards, looks like the counsel of wisdom. It however is dangerous if it flips mandates to requiring organizations to cooperate around new or far more variables, using information they will not have or cannot obtain, for all manner of interconnected scenarios, which if treated with equal seriousness, produce considerable modeling and analytic uncertainties.

VI

Just as risk and uncertainty differ in critical infrastructures (probabilities and consequences of failure are variously known or not), so too reliability and safety are not one and the same. Just because you reduce risk doesn’t mean you thereby improve safety. It is true that risk and safety overlap as terms in ordinary language. Some seek to formalize the purported relationships—e.g., increasing safety barriers reduces risk of component or system failure.

In contrast, I come from a field, policy analysis and management, that treats safety and risk to be very different. Indeed, one of the founders of my profession (Aaron Wildavsky) made a special point to distinguish the two. The reasons are many for not assuming that “reduce risks and you increase safety” or “increase safety and you reduce risks.” In particular:

However it is estimated, risk is generally about a specified harm and its likelihood of occurrence. But safety is increasingly recognized, as it was by an international group of aviation regulators, to be about “more than the absence of risk; it requires specific systemic enablers of safety to be maintained at all times to cope with the known risks, [and] to be well prepared to cope with those risks that are not yet known.”. . .In this sense, risk analysis and risk mitigation do not actually define safety, and even the best and most modern efforts at risk assessment and risk management cannot deliver safety on their own. Psychologically and politically, risk and safety are also different concepts, and this distinction is important to regulatory agencies and the publics they serve. . . .Risk is about loss while safety is about assurance. These are two different states of mind.

C. Danner and P. Schulman (2019). Rethinking risk assessment for public utility safety regulation. Risk Analysis 39(5), 1044-1059

Once again, the differences come with the failure scenarios—risks with respect to this failure scenario’s set of granularities as distinct from safety with respect to a different set of granularities or even a different failure scenario altogether.

VII

That failure scenarios do differ is nowhere better demonstrated than in the fact that there are different fields of infrastructure studies. For a world where bureaucratic and authoritarian states exert infrastructural power to further their own interests—well, that is the failure of concern. But there are other schools of infrastructure studies. Here I focus on what a socio-cultural perspective has to say about infrastructure repair that a socio-technical perspective might wish to pursue further. Since my work is from the socio-technical perspective, it’s only fair that I not try to summarize positions from a socio-cultural perspective but quote from their work directly:

For all of their impressive heaviness, infrastructures are, at the end of the day, often remarkably light and fragile creatures—one or two missed inspections, suspect data points, or broken connectors from disaster. That spectacular failure is not continually engulfing the systems around us is a function of repair: the ongoing work by which “order and meaning in complex sociotechnical systems are maintained and transformed, human value is preserved and extended, and the complicated work of fitting to the varied circumstances of organizations, systems, and lives is accomplished” . . . .

It reminds us of the extent to which infrastructures are earned and re-earned on an ongoing, often daily, basis. It also reminds us (modernist obsessions notwithstanding) that staying power, and not just change, demands explanation. Even if we ignore this fact and the work that it indexes when we talk about infrastructure, the work nonetheless goes on. Where it does not, the ineluctable pull of decay and decline sets in and infrastructures enter the long or short spiral into entropy that—if untended—is their natural fate.

S. Jackson (2015) Repair. Theorizing the contemporary: The infrastructure toolbox. Cultural Anthropology website. Available at: https://culanth.org/fieldsights/repair (accessed 24 September 2015)

The nod to “sociotechnical systems” is welcome as is the recognition that these systems have to be managed–a great part of which is repair and maintenance–in order to operate. Added to routine and non-routine maintenance and repair are the just-in-time or just-for-now workarounds (software and hardware) that are necessitated by inevitable technology, design and regulatory glitches–inevitable because comprehensiveness in analysis and operations is impossible to achieve in complex large-scale systems.

For its part, socio-technical research on infrastructures calls into question any assumption that macro-designs control every important micro-operation, an assumption also very much questioned in this socio-cultural perspective, e.g., “approaching infrastructure from the standpoint of repair highlights actors, sites, and moments that have been absented or silenced by stories of design and origination, whether critical or heroic.” Here the test of efficacy isn’t ‘‘Have we designed a system that can be controlled?,’’ but rather ‘‘Is this a system we can manage to redesign as needed?’’

Also from the socio-technical perspective, the “end of infrastructure operations” isn’t decay, decline or entropy from a socio-cultural perspective as much as system failure and immediate emergency response, including seeking to restore, as quickly as possible, even if temporarily, water, electricity and telecoms to survivors. What to my knowledge has not been pursued in the socio-technical literature is the following from a socio-cultural focus on repair:

Attending to repair can also change how we approach questions of value and valuation as it pertains to the infrastructures around us. Repair reminds us that the loop between infrastructure, value, and meaning is never fully closed at points of design, but represents an ongoing and sometimes fragile accomplishment. While artifacts surely have politics (or can), those politics are rarely frozen at the moment of design, instead unfolding across the lifespan of the infrastructure in question: completed, tweaked, and sometimes transformed through repair. Thus, if there are values in design there are also values in repair—and good ethical and political reasons to attend not only to the birth of infrastructures, but also to their care and feeding over time.

That the values expressed through repair (we would say, expressed as the practices of actual repair) need to be understood as thoroughly as actual design reflects, I believe, a major research gap in the socio-technical literature with which I am familiar (the latter being much more concerned with the gap between designs-to-control and practices-for-managing/coping). Finally, I cannot over-stress the importance of infrastructure fragility, contrary to any sturdy-monolith imaginary of infrastructural power one might have gotten from elsewhere.

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[1] Not only is societal dread important, but so is operator distrust. One reason infrastructure operators manage reliably is that they actively distrust the future will be stable or predictable in the absence of the system’s vigilant real-time management. We of course must wonder at the perversity of this. But that is the function of this dread and distrust. Namely: to push all of us in probing further what it means to privilege reliability and safety over other societal values. We are meant to ask: What would it look like in world where such reliability and safety are not so privileged? For the answer to that question is again obvious: Most of the planet already lives in that world of unreliability and little safety. We’re meant to ask, precisely because that answer is that clear.

Introduction

One central insight from the literature and theory of High Reliability Organizations (HROs) is that past reliable performance of large socio-technical systems does not predict, let alone ensure, reliable performance into the future. In this sense, then, there are two futures of interest in this blog entry: the future of large socio-technical systems from the perspective of HRO Studies and the future of HRO Studies.

It’s to be recognized from the get-go that “HRO Studies” now houses many reliability-seeking rooms. A major path trajectory for research and taxonomies has been the early work of Todd LaPorte, Gene Rochlin, Karlene Roberts and Paul Schulman around a set of hazardous organizations mandated to maintain reliable (safe and continuous) operations (LaPorte and Consolini 1991; Roberts 1993; Rochlin 1993; Schulman 1993). We need look no further for the durability of this trajectory than the many comparisons of HRO/HRT (high reliability theory) to Charles Perrow’s Normal Accidents Theory (more recently, Bamburger 2014 for cybersecurity; Min and Borch 2021 for financial markets).

Yet, it is also true that HRO Studies has been extended and changed in ways initially unforeseen with contributions to, inter alia, management practice (e.g., Weick and Sutcliffe 2001), safety science (e.g., Hopkins 2014; Amalberti 2013), resilience theory and practice (e.g., Hollnagel, Woods, and Leveson 2006; Boin and van Eeten 2013), networked reliability (e.g., de Bruijne 2006; Roe and Schulman 2016), and analyses of high reliability as a continuous quantifiable variable in the operations of health care, nuclear power, and other industries (Vogus and Sutcliffe 2007; Schöbel 2009; May 2013; O’Neil and Kriz 2013).

In additiion, other fields, like development studies, have also drawn water from this wider trough (Scoones 2024). Most notably for our purposes here, this diversification of HRO Studies has witnessed a shift from identifying HRO properties or features at a point in time to identifying processes of high reliability organizing and managing over time (e.g., Ramanujam and Roberts 2018). Another piece of evidence for the continuing relevance of HROs, now writ large, is the Google Ngram for the term “high reliability organizations” shows a steady climb in the literature.

That said, as there is something perverse in assuming past trends and growth are a reliable guide for the future of and in HRO Studies, how then to see better what’s ahead for the field and what’s ahead by way of large socio-technical systems?

Specific aim

My answer is to return to another, more methodological insight of LaPorte, Rochlin, Roberts and Schulman: The specific cases analyzed matter profoundly. In their set, they found reliable management at that point in time where theory would still tell you not to expect it.

But, of course, there were other reliability-seeking cases and unsurprisingly some of these did not and still do not exhibit HRO processes, let alone features. That indeed is the lesson I take away from the many published “HRO v NAT” comparisons: not that one theory is better “overall” than the other, but that there is still no substitute for attending to differences in the cases examined, in time and over time–especially if theory is to matter for practice.

Focus, rationale and roadmap

I want to suggest then that HRO Studies might benefit at this juncture by a comparative and longitudinal analysis involving similar or related cases. I am familiar with only one, that starting with the California Independent System Operator (CAISO), which operates most of the state’s electric transmission grid.

Here I focus on the aforementioned “network reliability” strand of HRO Studies and ask: What have we learned since Mark de Bruijne published his transmission grid study of CAISO in 2006? I start with this work for three reasons: His book preceded our own 2008 work on managing networked high reliability in electricigty transmission; we aligned subsequent work with De Bruijne and others (Roe and Schulman 2016: 10); and I want to be very transparent upfront that I am not cherry-picking quotes from our own work to substantiate the implications drawn at the end of this blog entry.

Both Paul Schulman and I continued the CAISO research and analysis after our Dutch colleagues left, the results of which were in the form of updates and framework extensions in Roe and Schulman (2008, 2016). More recently, Paul Schulman and I have investigated the notion of network reliability across interconnected critical infrastructures, including but not limited to electricity (Roe and Schulman 2018, 2023).

In what follows, I first present De Bruijne’s findings. I then update this earlier notion of networked reliability in light of our research to the present on interconnected critical infrastructures, including that of electricity. The conclusion focuses on what I take to be important implications for the network reliability, both as a strand in HRO Studies and in the future(s) of large socio-technical systems. To telegraph ahead and in T.S. Eliot’s words, “the end of all our exploring will be to arrive where we started and know the place for the first time.”

Summary of Networked Reliability (de Bruijne 2006)

The full text of Mark de Bruijne’s Networked Reliability is well worth reviewing and can be accessed at https://www.researchgate.net/publication/306011428_Networked_Reliability_Institutional_fragmentation_and_the_reliability_of_service_provision_in_critical_infrastructures.

For those who do not have the time, the work is summarized in a 2007 article De Bruijne co-authored with his dissertation advisor and our early CAISO research colleague, Michel van Eeten, “Systems that Should Have Failed: Critical Infrastructure Protection in an Institutionally Fragmented Environment” (accessed at https://www.researchgate.net/publication/227701135_Systems_that_Should_Have_Failed_Critical_Infrastructure_Protection_in_an_Institutionally_Fragmented_Environment)

I quote at length from De Bruijne and Van Eeten in order to establish for later purposes of comparison a separate and uninterrupted benchmark for the networked reliability then under study in the early 2000’s:

A key question that arises from these developments is: how do CI [critical infrastructure] industries, consisting of networks of organizations, many with competing goals and interests, provide reliable services in the absence of conventional forms of command and control? This raises another question that, logically, precedes it: are institutionally fragmented CIs in fact still reliable?

Does Institutional Fragmentation Affect the Reliability of Service Provision?

The exact relationship between institutional restructuring and the reliability of services and networks has so far remained largely obscured. The available empirical data on reliability – measured in terms of the frequency and length of disruptions to end-users – fail to provide an unequivocal answer. We were able, however, to draw upon extensive field research on reliability-related issues in large-scale water systems (Van Eeten and Roe, 2002; Roe and Van Eeten, 2002), electricity grids (Schulman et al, 2004; Roe et al, 2005) and telecommunication networks (Van Eeten et al, 2005; De Bruijne, 2006). Together, these field studies comprise over 130 interviews, extensive control room observations and literature reviews.

Without repeating previous discussions of our findings, we can draw out a number of implications, primarily based on our studies in electricity and telecommunications. First of all, while there are no conclusive data regarding the reliability of services and networks post-restructuring [post-deregulation, privatization and liberalization], the data that is available suggests that the network operators and service providers have managed to cope with these changes. The two focal organizations that we studied – the California Independent System Operator (ISO) and Dutch mobile telephony operator KPN Mobile – succeeded in maintaining a high reliability of service provision. The organizations displayed virtually unchanged levels of service provision before and after restructuring. The ISO’s reliability performance during California’s electricity crisis in 2000 and 2001 – one of the most turbulent periods in which any restructured critical infrastructure industry ever operated – did not lead to outage rates that differed significantly from those of the utilities before restructuring. In the end, the lights stayed on for most of the time, notwithstanding the popular images in the media of sweeping blackouts across. The reported rolling blackouts occurred on eight days for 27 hours, compared to the 125 days on which just 1.5 percent of operating reserves remained and stage 3 emergencies were declared. The aggregate amount of load shed during California’s electricity blackouts was quite small, adding up to no more than one hour’s worth of electricity to all residential homes in the state. This performance fell within the margins of the average annual reliability performance of the investor-owned utilities before restructuring. However, other key reliability indicators (e.g. the number of high-voltage transmission line overloads and the number of violations in the ISO’s control area) did show that the system was operating closer to the edge of failure – demonstrating the massive pressure under which the system was operating. In other words, although negative effects of restructuring could be identified, the organizations involved, most notable the ISO, managed to cope with these effects and maintain acceptable levels of service and network reliability.

Similarly, the Dutch mobile telephone operator KPN Mobile displayed a steady reliability performance from 1996 to 2001, notwithstanding seven-fold increase in customers, the rapid expansion and innovation of its mobile network and the six-fold increase in the number of services it provided over this network. From 1996 to 2001, the company displayed steadily rising call completion rates (CCR) and call setup success rates (CSSR), which in the telecommunication industry are considered key proxies for the reliability of service provision. In addition to these steadily improving reliability indicators, KPN experienced ‘only’ a 50 percent increase in the number of ‘calamities’ – which they define as incidents with an impact on customers.

While significant, this number pales in comparison to the growth rate of customers, network and services. KPN Mobile achieved this performance under cut-throat competition in the market which forced them to undertake drastic cost reductions in their operations.

Considering the effects of institutional fragmentation on how these CIs were organized and operated, the abovementioned performance of both the ISO and KPN Mobile may be considered an astonishing feat. Despite operating under conditions with significantly reduced resources time and again the organizations managed to maintain a reliable provision of CI services. These findings are all the more puzzling since the two dominant organizational theories that are used to assess the reliability, or lack thereof, of complex, large-scale technological systems would predict a negative impact on the ability of organizations to reliably manage these CIs.

The Normal Accident Theory (NAT) (Perrow, 1999a) and High-Reliability Theory (HRT) (Roberts, 1993) both expect that institutional fragmentation caused by restructuring negatively affects the ability to reliably manage these infrastructures and that reliability of service provision accordingly should have suffered. However, the case studies did not confirm the theoretically assumed negative relationship between the effects of institutional fragmentation and ability to reliably manage these infrastructures even though infrastructure operations did become more complex to manage and behaved more volatile (De Bruijne et al., 2006). Evidence did show that the infrastructures operated ‘closer to the edge’ than before restructuring. So how can we explain the performance record of restructured CIs and the more or less continued high reliability of the provided services in the researched cases?

Coping with institutional fragmentation

Based on these findings, it could be concluded that institutional fragmentation and restructuring not only negatively affected the ability of organizations that manage CIs to provide highly reliable services, but also offered new options that enabled organizations involved in the management of these systems to maintain reliability under extremely demanding conditions. The case studies revealed a large number of hitherto unknown or unrecognized conditions that enabled these organizations to cope with the effects of institutional fragmentation (De Bruijne, 2006). Examples include the increased use of real- time, on-line experimenting; the gradual redefinition of reliability norms and criteria to fit the new conditions and the increased use of support staff and informal wheeling and dealing in real-time in control rooms. These conditions, which many at first glance would consider detrimental to the provision of reliable services, were found to contribute to the ability of the organizations to maintain a reliable provision of services.

The research found both NAT and HRT flawed in their assumptions on the main relationships between the conditions that facilitate reliability and the levels of reliability achieved. The networked environment clearly emphasized different reliability-enhancing characteristics than those identified by NAT and HRT (cf. Grabowski & Roberts, 1996; Schulman et al., 2004). The implication is that NAT and HRT, which until now have been presented as generic organizational theories of (un)reliability, need to be modified in order to be valid under conditions of networked reliability (see also Schulman et al, 2004; De Bruijne, 2006). In general terms, we have identified three shifts of emphasis in organizational processes and resource allocation.

(i) From long-term planning to real-time management

Institutional fragmentation and the introduction of competition create more volatile and technologically more complex infrastructures. Many of the procedures and routines that had been designed to reliably operate the CIs do not function anymore. Infrastructure operations used to emphasize the importance of complete information, centralized planning and command and control. Institutional fragmentation caused those in control of infrastructure operations to be confronted with less than adequate information and control, leading to more surprises and reliability-threatening events. This in turn emphasizes a need for more flexible response capability to maintain reliable services. Real-time operations – typically focused in and around control centers – increases in importance, reducing the strong reliance on long-term, detailed planning that has characterized CIs (cf. De Bruijne et al., 2006; Van Eeten et al., 2006; Roe et al., 2002).

(ii) From design and analysis to improvisation and experience

More volatility and complexity also means more unpredictability. As Demchak (1991, p. 3) has said, the chief manifestation of complexity is surprise. Operations move more often ‘outside analysis’, beyond the well-studied situations for which technology has been designed and procedures have been tested. Under these circumstances, relying on established procedures, routines and guidelines decreases rather than ensures reliability. In real-time, control room operators increasingly have to rely on their experience and improvisational abilities to deal with surprises and volatile events. Referential knowledge, improvisation, ‘instinct’ and experience gain precedence in comparison to detailed procedures and routines. It becomes more important to train operators to know when not to follow procedure and how to still maintain reliability.

(iii) From standardized and formal to real-time informal communication and coordination

The third shift moves infrastructure operations away from formal and hierarchical towards informal and ‘rich’ modes of communication and coordination. To put it differently: real-time resists formalization. Faced with surprises and threatening events, CI operations are constrained by hierarchical, unilateral, and formal modes of communication and coordination; albeit legacies from the pre-restructuring days or those installed after restructuring to ensure competition and level playing fields. Both types severely handicap operators’ abilities to improvise and provide reliable services. Especially when faced with reliability-threatening events, informal communication and coordination mechanisms take over or augment formal mechanisms. The need for real-time communication has already been identified in the literature on coordination in networks of organizations as well. In the absence of formal communication and coordination arrangements between organizations in networks, informal coordination and communication evolve and take over (cf. Chisholm, 1989). Powell (1990:304) finds information passed through networks (of organizations) must be “thicker” than information obtained through markets and “freer” than information communicated through hierarchies.

Real-time, ‘rich’ informal communication and coordination has been identified as one of the most important sources of networked reliability: “[R]eal-time values and privileges the non-routine over the routine, the informal over the formal, and the relational over the representational” (Roe et al., 2002:9-5). In other words, the ability of system operators to engage in a rich exchange of information and informal deals enhances their knowledge of system conditions, stimulates creativity and increases their options for maintaining reliability. To be sure, under ‘normal’ operating regimes, the need for ‘rich’ and varied communication and coordination is constrained by the competitive environment in which CIs nowadays operate. However, when threats occur and move towards real-time, ‘rich’ and informal communication and coordination become increasingly important. Real-time informal infrastructure operations enable types of interventions and control that are typically unacceptable at any other time or place.

(endnotes deleted for readability; citations kept in order to date the findings in the quoted text)

How this picture has changed to the present

As Paul Schulman and I were never invited back to CAISO after 2008, nothing in what follows can be interpreted as remarks about that grid transmission manager today. It should, however, be noted that we did find further evidence of CAISO moving closer to the edge of reliability performance with the introduction of new systemwide marketing software (Roe and Schulman 2016).

Rather than CAISO specifically, what is of interest here is a comparison and update of the notion of networked reliability scanned in the above quote and updated in our subsequent work (most recently, Roe and Schulman 2023).

For me, the most striking contrast is this: Some of us in this networked reliability strand of HRO Studies are having to spend considerable time on parsing out the features and processes of the interconnectivities between and among the networked critical infrastructures.

Stay with electricity as the example. The network of primary interest is no longer the one connecting the then-fragmented, deregulated units for generation, transmission and distribution of the once integrated energy utilities. Today’s electricity network of interest revolves how it is interconnected with other “lifeline” infrastructures, not least of which are the large socio-technical systems for water, telecommunications and transportation.

Further, the configurations of these interconnections are far more varied than originally studied for maintaining the continuous provision of a critical service, even during (especially during) turbulent periods. Serial dependencies and reciprocal interdependencies are matched by pooled and mediated interconnectivities in a wide variety of permutations and combinations. Empirically, many more versions of Interconnected Critical Infrastructure Systems (ICISs) can be identified and demonstrated than even system modelers acknowledge to date (Roe and Schulman 2016).

One of the ironies of having this now-wider understanding of network interconnectivities is that the picture has become more granular and detailed for purposes of operations and management than was the case for in describing the restructured utilities. The centrality of human ingenuity under urgent circumstances moves beyond the control room and into the field in periods of system disruption, failure, immediate emergency response and initial service restoration. “Rich” informal communications and coordination take place between different infrastructure staff when their respective system control variables overlap or are shared (e.g., the railroad bridge over a major shipping navigation way becomes stuck). In fact, there are cases where improvisations undertaken together by the different infrastructures, field staff and/or control rooms, are the real-time interconnectivities that matter for the respective operations.

Initial implications

Just as the extended quote of De Bruijne and Van Eeten is date-stamped by the then very live issue of energy deregulation, so my preceding update will be seen as date-stamped by what is today’s headline issue of emergency management in a world of interconnected critical infrastructure faced by all manner of crises.

But such dating is not the problem here. What remains a problem is that finding in De Bruijne and Van Eeten: “The research found both NAT and HRT flawed in their assumptions on the main relationships between the conditions that facilitate reliability and the levels of reliability achieved. The networked environment clearly emphasized different reliability-enhancing characteristics than those identified by NAT and HRT.” We–and I include myself here–are still being astonished by higher levels of reliability performance than current theories and expectations would expect us to believe. Aspirational high reliability seems to be transformed into high reliability management at least in some cases and without any guarantees for doing so in the future. To say this can’t go on forever is hardly the point; rather: How is this still happening?

How did CAISO survive the introduction of its disruptive the then-new system marketing software that we studied? How has China’s high-speed rail system been as reliable as it has been, given its massive size and scale? Does the capacity to achieve reliable normal operations in digital platforms–not by precluding or avoiding certain events but by adapting to electronic component and subsystem failure most anywhere and most all of the time–offer a very different skill-set for “reliability management” in other digitized critical infrastructures? Are there in fact more “control rooms” and “reliability professionals” out there than those of us who study them acknowledge?

Note in asking these questions I am reproducing the same level of astonishment and question-asking that motivated the earliest HRO researchers with respect to the systems they studied. If so, studies of networked reliability–and HRO Studies as a whole?–have always had a future in search of more answers.

References [to be provided]

International legal change is an affair of societal and institutional practices about and around legal norms. Observe these practices, the social facts and not just the texts,. . .and you will see the real dynamics of international legal change. Nico Krisch recently took the matter to heart, and identified five paths of change in international law through social facts: the state action path (‘when states modify their behaviour and make corresponding statements’); the multilateral path (when ‘change is generated as a result of statements issued by many states within the framework of an international organization’); the bureaucratic path (through ‘decisions or statements produced by international organizations in contexts that do not involve the direct participation of states in the decision- making process’); the judicial path (change through ‘decisions and findings of courts and quasi-judicial bodies’); and the private authority path (where ‘change follows statements or reports by recognized authorities in a private capacity without a clear affiliation to or mandate from states or international organizations’, typically taking the form of ‘the production of technical manuals, standards, and regulations’).

https://www.cambridge.org/core/journals/leiden-journal-of-international-law/article/international-law-in-the-minds-on-the-ideational-basis-of-the-making-the-changing-and-the-unmaking-of-international-law/F7CE42451E97CCF68A87239E6E3485CF

If indeed multiple pathways are required to assess international legal change(s) with respect to pastoralists worldwide, then that topic, “international legal change in pastoralism,” is one ripe for study and action.

Some comparative studies of pastoralists across regions or in terms of World Bank, IMF and other IO programs, along with fewer comparisons of policy and management differences between relevant International NGOs, to which we can add some analyses of cross-country court cases and of international regulations governing the many aspects of livestock production and export hardly constitute a coherent foundation for describing the relevant international legal changes.

I’m just as guilty as others in habitually collapsing the legal under the rubric of “policy and management.” In advance of the 2026 International Year of Rangelands and Pastoralists. however, we are better advised to take greater care in separating the legal out from the rest in the next steps ahead. This is especially true, I believe, where pastoralist systems are a dominant infrastructure for generating options variety in the face of high uncertainty and complexity (the legal becomes much more obvious and relevant in infrastructure studies).

Consider “the unimaginability of any alternative to the neoliberal status quo.” Surely that’s a glove pulled inside-out. Neoliberalism generates such contingency and uncertainty as to undermine any status quo. It’s the status quo that is unimaginable.

Then again, have status quo’s ever been in practice as they are in theory? To paraphrase the international relations theorist, Hans Morgenthau: Excuse me, but just what status quo have the people committed themselves to? They haven’t, irrespective of what systems are said to do by virtue of their own structures. In situations where indefinite recovery is the new normal, what does the status quo ante even mean today?

. . .we knew the murderer in Edwin Drood because Dickens did actually tell his illustrator: “I must have the double necktie! It is necessary, for Jasper strangles Edwin Drood with it”;

. . .Henri Bergson were the sole example of a philosopher having an unprecedented impact on everyday life, as he’s said to have caused the first Broadway traffic jam in New York City;

. . .Shakespeare should be criticized because he failed to mention that poor people, not just kings, have trouble sleeping (Henry IV, Part 2, act III, scene 1);

. . .the 175 – 200 million workers in China’s factories, mines and construction industry weren’t the world’s largest proletariat;

. . .the only genuine political project were setting tax rates on the rich and emergency management were primarily a matter of “it can’t happen here’; and

. . .”don’t give a man a fish, but teach him how to fish” is now: If one has to fish, ensure the ecosystem bounces back nevertheless.

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