Heuristics as clues

When Louis XIV saw the new maps of France he sponsored in 1693 he supposedly complained that his cartographers had cost his kingdom more land in a year than foreign armies had done in a century.

(From Paul Slack’s The Invention of Improvement)

–Long-held heuristics, like routines and standard operating procedures, are shorthand ways of doing things without all the uncertainty of reinventing the wheel. Newer heuristics include big data algorithms we don’t understand and policy narratives we think we do, both of which enable making decisions in the face of uncertainty. Both shorthands are treated as good-enough, like a new atlas of maps.

The older heuristics are relied upon because they are said to reduce uncertainty; more recent ones are used to better manage (in the face of) uncertainty that hasn’t been/cannot be reduced, at least for the moment.

One major commonality between both the old and new needs to be highlighted. While typically not taken as such, both are less a shorthand than clues for what to do ahead.

–By way of example, handbooks detailing how to respond to unpredictable floods and famines were written by and for administrators in Imperial China. Over the course of some thousand years, handbooks started to group together what had been learned into tables of maxims (sometime cast in rhyme) for ease of reference by users.

Handbooks “are quick to insist, however, that using the tables is not sufficient in the long run: for the professional administrator they are rather a ‘clue’. . .that indicates where to go in the more complete texts,” writes Pierre-Étienne Will, the most recent and comprehensive bibliographer of handbooks (2020, XLIV). This status of heuristic-as-clue is to alert us to important omissions that require reference beyond any shorthand exposition (Ibid, 568). Occasions when a map proves imperfect and misleading are all too familiar.

Professor Will elaborates in an email: “’clue’ (yinxian 引線. . .) literally means ‘a thread that leads to…’, ‘that can be pulled to get…, or something of the sort. The same character yin is part of the words suoyin and yinde, meaning ‘index’, in modern Chinese. The tables or rhymes are like indexes to the complete texts.”

–I want to apply this notion of heuristic-as-clue more speculatively to the newer algorithms derived from big data. We’re told that, even though the algorithms are not based on models of known cause and effect, they identify complex, albeit opaque, correlations said to be worth relying upon.

But that stops short of the needful. The status of a heuristic as clue underscores that, just as with causal models, there’s also a great deal yet to puzzle out with correlations before going forward. Correlations are not just the start of an analysis. They also are in context and those contexts start the analysis as well. Correlations index spatial-temporal references to be pursued.

–There is no obvious point of entry when it comes to revealing the wider references. For purposes of illustration, start with the canonical index of fire, smoke. In the same way, the heat from server centers (some indeed call it “data exhaust”) indexes the large electricity usage in generating and updating algorithms. But context doesn’t stop there. Other clues are less spatial-temporal and more social for the heuristic inseparable from wider referential meanings.

Again, by way of example, the status of the algorithm-as-heuristic clues you into the underlying assumptions for using big dataset algorithms, not least of exemplify “trust.” Some say, e.g.:

  • algorithms deliver the best result among the other methods and heuristics available;
  • while not free of bias, they do a better job than others by virtue of the huge run of cases and calculations;
  • some kind of result at the scale of big data is better than no result, plus the algorithmic result is often more timely; and
  • anyway, there’s always a danger that the critics of big data algorithms take them more seriously than the users, like consumers who comparison-shop and then make their own decisions.

The wider point here is that the methodological duty of care in using heuristics means treating them as indexes of that which cannot be omitted, or could have already been omitted, from analysis and practice when usefulness is the question.

Principal sources

Pierre-Étienne Will (2020). “Introduction,” in: Handbooks and Anthologies for Officials in Imperial China: A descriptive and critical bibliography. Koninklijke Brill NV, Leiden, The Netherlands.

The notion of index in the sense of smoke and fire follows that of C.S. Pierce (“purse”), a founder of American pragmatism.

R. Machen and E. Nost (2021). “Thinking algorithmically: The making of hegemonic knowledge in climate governance.” Transactions of the Institute of British Geographers: 1-15.

Julia Velkova (2021). “Thermopolitics of data: Cloud infrastructures and energy futures.” Cultural Studies.

What to do when policy articles keep ending where they should’ve started

In an analysis of 35 recent literature reviews on security implications of climate change, the authors point out:

A frequently voiced recommendation in reviews of the climate–conflict literature concerns a need for increasing methodological diversity and rigor. This research priority has multiple dimensions and, at the core, applies as much to the wider research field as to any individual study, given inherent complexities of combining diverse research methods and epistemologies within a single integrated analytical framework. Common calls include (1) application of mixed-methods research designs, (2) in-depth analysis of influential data points to trace the causal processes at play and to (3) triangulate and validate findings from the quantitative empirical literature, as well as (4) out-of-sample prediction to evaluate the generalizability of particular results and to explore long-term implications of alternative scenarios.

Calls for methodological diversity in the study of complex policy issues are a fixture to such an extent you have to wonder why new research doesn’t begin with that observation and follow through. Instead, the calls are a repeated finding to be dealt with whenever.

–One reason is that no such research could be funded for or undertaken by researchers as singletons. Not only would you need that imaginary of the interdisciplinary team with that long-term commitment, you’d need the funding of large foundations or government agencies that are worrying about other things.

What could be more worrisome, you ask, than complex issues of climate change and conflict? Foundations and government agencies suspect, if not already know, that major research programs routinely identify more questions than answers. “It turns out we’re not even asking the right questions. . .,” so goes the key finding.

So, what’s the upshot? Are there useful things we can do now?

Experience tells us there are at least five upshots right in front of us but often not seen:

1. Don’t forget the big-five prism.

People’s perceptions of a complex policy problem vary by their: age, education, income/class, gender and race/ethnicity. Of course, the categories are socially constructed (e.g., some governments do not gather data by “race”). But they are meaningful precisely because of that. Other factors, like sexual orientation or language are as important, if not more so, for contexts as differentiated as they are.

You can’t assume your audience and even other policy types appreciate the importance of these demographic filters.

2. The status quo is always an alternative, just as are better practices developed elsewhere and modified for the case at hand.

It’s too often said that “because the status quo is untenable, we must find an alternative.” Actually, “maintain the status quo” is among the alternatives to be evaluated.

The status quo is “business as usual,” not the “Do nothing” option. Under the status quo (e.g., the agency continues to do what it is already doing), one option is whether the activities already underway could achieve the ends sought, eventually. This is important because of that other probability–not just possibility–when implementation of new option leads to conditions worse than the status quo.

Also, it would be astonishing in a planet of 7.5+ billion persons that people elsewhere were not thinking about the complex issue in question or had already moved on to practices that deal with it or like issues.

In short, if you are searching for a radical alternative to the status quo, first satisfy yourself that there aren’t status quo’s already radicalized and modifiable for your purposes.

3. Some complex policy problems are complex because not everything is in a trade-off.

Just as with “risk,” “trade-off” has become such a naturalized term of policy-talk that people ask right off, “Well, what are the risks and trade-offs involved?”

But talk of trade-offs is premature for a number of hard issues. Infrastructure high reliability assumes a theory of nonfungibility, where nothing can substitute for the high reliability and safety without which there would be no markets for goods and services, at least for right now for the economically allocative decision. Economics, in contrast, is a theory of substitutability, where goods and services have alternatives in the marketplace.

4. Evaluations of complex policy interventions find mixed results but less frequently identify trade-offs over “what’s enough?”

Because policy analysis has been from its inception an interdisciplinary profession, it is also multi-criteria for the purposes of assessing options before implementation and evaluating results afterwards.

The more criteria that options are evaluated with respect to–efficiency (benefits over cost), cost effectiveness (e.g., largest benefits for a given cost or budget), political feasibility, administrative feasibility, legality, and others (e.g., equity, sustainability. . .)–the more unlikely straightforward success is achieved. The common response has been to reduce the number of criteria or insist some–efficiency and cost-effectiveness, most notably–take priority.

Yet a very different reaction to typically mixed results is to insist that, where trade-offs do exist, they are about having enough of each. More, the second you admit into decisionmaking questions of “what is enough?,” feasibility criteria rapidly focus on: Which alternative, if implemented, can keep decisionmaker options open for unpredictable changes ahead?

5. Nothing is implemented as planned (but often not for reasons you think).

Hardly news, the reasons given for the gap between what’s planned and what’s implemented typically refer to politics, dollars and jerks. Even where so, the statement needs to be pushed further, with conditions being as differentiated as in complex issues.

A fuller explanation for the shortfall is that policy formulation is usually based on cause-and-effect analysis, while implementation is usually undertaken in terms of means-and-ends considerations. The gap to be worried about is not so much between plan and implementation as it is between cause-and-effect thinking and means-and-ends thinking.

People on the ground implementing don’t see themselves as “the effects” of “external causes”. They hold themselves to be actually existing human beings with really existing goals requiring real means to achieve them. This is also why experience with implementation and operations is so important: We can never assume things will get implemented by means and ends if analyzed or predicted in terms of cause and effect.

–A concluding point about that “experience with implementation.” More experience does not mean less inexperience with complexity.

To repeat earlier entries, the more experience with complexity we have, the more aware we are of how inexperienced we remain and of new difficulties ahead. As a wit would have it, such is peer-review by reality. Always having new questions to ask is only an epiphenomenon of persisting inexperience and difficulty.

Principal sources

von Uexkull, N. and H. Buhaug (2021). “Security implications of climate change: A decade of scientific progress.” Journal of Peace Research 58(1): 3 – 17.

Previous blog entries: “What am I missing?,” “Poverty and war,” “Some answers,” “Short and not sweet,” “Inexperience and central banks,” “Difficulty at risk and unequal”

Predicting the future

[Ulrich] suspects that the given order of things is not as solid as it pretends to be; no thing, no self, no form, no principle, is safe, everything is undergoing an invisible but ceaseless transformation, the unsettled holds more of the future than the settled, and the present is nothing but a hypothesis that has not yet been surmounted. (Robert Musil, novelist)

–The future’s unpredictability is not something up ahead or for later on, but is instead present prospection. One implication is that to predict the future is to insist we manage the present in different ways.

Indeed, the notion that what will save us ahead has yet to be invented misses the point that pulling out a good mess or forestalling a bad mess or taking on different messes today is the way to change tomorrow. The only place the future is more or less reliable is now, and only if we are managing our messes, now.

–This also 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.

Now: What’s a good mess to be found in this huge uncertainty and unstudied conditions? Do we assume, by way of an example, Global Climate Change is going to affect all insect species? How would we model that? Insects may not matter to you, but they do matter to millions and millions of other people. Yet, some 1 million insect species have been identified in a world of possibly 30 million insect species.

–Yes “of course,” Planet Earth is a closed system, but equally closed with respect to everything? In my view, the mess we’re in–and it’s a good mess–is that this global crisis, like others, can’t be about the planet and science, all the way down. All the way down takes us quickly to all manner of “yes, but. . .”

Table of key entries by topic area

Most Important: “What am I missing?,” “Complexity is the enemy of the intractable,” “Power,” “Interconnected?,” “I believe,” “Wicked problems as a categorized nostalgia,” “Even if what you say is true as far as it goes, it doesn’t go far enough…,” “Triangulating complexity for policy and management,” “Time as sinuous, space as interstitial: the example of total control,” “Keeping it complex. . .,” ““Long-terms, short-terms, and short-termism,” “More on over-complexification,” “Playing it safe, utopia,” “Case-by-case analysis: realism, criteria, virtues,” “Not ‘Why don’t they listen to us?’ but rather: ‘What should we listen for from them. . .’,” “Humanism, by default,” “Mess and reliability: five inter-related propositions,” “Control, surpris’d,” “When good-enough is better: a summary,” “Heuristics as clues”

Recasting big policy issues: “Poverty and war,” “Second thoughts on income inequality,” “Surprising climate change,” “COVID-19,” “Missing racism,” “Healthcare,” “To-do’s in the Anthropocene, ” “The market failure economists don’t talk about: Recasting infrastructures and the economy,” “Culling sustainability,” “In a failed state,” “Revolts,” “A colossal inheritance,” “Wicked problems as a categorized nostalgia,” “Making the best of linear thinking, complexly: typologies for reframing ‘coordination’,” “Government regulation,” “Economic consequences of having no must-never-happen events in the financial sector,” and Longer Reads (below)

More recastings: “Policy narratives,” “America’s and Trump’s,” “Recastings #1,” “When the light at the end of the tunnel is the tunnel,” “Public Policy Analysis, c.1970 – c.2020: In Memoriam?,” “Sound familiar? Here’s why,” “A grammar of policy analysis,” “Bluejays, fists and W.R. Bion,” “Policy as magical thinking,” “A different take on ‘traditional agriculture:’ risk-averse v. reliability-seeking,” “Finding the good mess in supply and demand,” “Escaping from Hell Is a Right!,” “Global Climate Sprawl,” “Disaster averted is central to pastoralist development,” “Narrative policy analysis, now and ahead”

Not-knowing and its proxies: “Seeing unknowns,” “Inexperience and central banks,” “Managing inexperience,” “Difficulty at risk and unequal,” “By way of distraction…,” “Shakespeare’s missing lines still matter,” “Humanism, by default”

Ignorance and uncertainty: “When ignorance does more than you think,” “Optimal ignorance,” “Uncertain superlatives,” “Stopping rules and contested regulation,” “To-do’s in the Anthropocene,” “Why aren’t they all running away!,” “Yes, ‘risk and uncertainty’ are socially constructed and historicized. Now what? The missing corollary and 3 examples,” “Killing cognitive reversals,” “Error and Safety,” “Triangulating complexity for policy and management”

Risk, resilience and root causes: “A new standard for societal risk acceptance,” “Easily-missed points on risks with respect to failure scenarios and their major implications,” “Risk criteria with respect to asset versus system scenarios,” “Half-way risk,” “Central role of the track record in risk analysis,” “Resilience isn’t what you think,” “Root causes,” “Frau Hitler, again,” “With respect to what?,” “Yes, ‘risk and uncertainty’ are socially constructed and historicized. Now what? The missing corollary and 3 examples,” “Error and Safety,” “Four macro-design principles that matter—and one that can’t—for risk managers and policymakers,” “Managing-ahead for latent risks and latent interconnectivity,” “Can’t we be best anticipatory and resilient at the same time?,” “Safety, like much in democracy and intelligence, is not a noun but an adverb”

Regulation: “A few things I’ve learned from the Financial Times on regulation,” “Government regulation,” “Stopping rules and contested regulation”

Infrastructures: “The real U.S. infrastructure crisis,” “Innovation,” “Take-home messages,” “Who pays?,” “When high reliability is not a trade-off,” “The market failure economists don’t talk about: Recasting infrastructures and the economy,” “When ignorance does more than you think,” “Catastrophizing cascades,” “Healthcare,” “Interconnected,” “Stopping rules and contested regulation,” “Achilles’ heel of high reliability management,” “Where distrust and dread are positive social values,” “To-do’s in the Anthropocene,” “Government regulation,” “Killing cognitive reversals,” “Error and Safety,” “Managing-ahead for latent risks and latent interconnectivity,” “What you need to know: Big System Collapse! Or not.”

Environment: “New environmental narratives for these times (longer read, consolidated from following entries),” “Nature,” “Tansley’s ecosystem,” “Radical uncertainty and new environmental narratives,” “Eco-labelling recasted,” “European Union Emissions Trading Scheme, Scenes I and II,” “To-do’s in the Anthropocene,” “Dining on gin and consommé,” “Culling sustainability,” “Lifecycle modeling of species,” “Better fastthinking in complex times,” Narrative policy analysis, now and ahead”

Rural development: “Disaster averted is core to pastoralist development,” “Optimal ignorance,” “Culling sustainability,” “A different take on ‘traditional agriculture:’ risk-averse v. reliability-seeking,” “Misadventures by design,” “Triangulating complexity for policy and management,” “Next-ism”

Catastrophe and crisis: “Catastrophizing cascades,” “Jorie Graham’s systemcide,” “The shame of it all,” “Next-ism,” “The future is the mess we’re in now,” “Killing cognitive reversals,” “Escaping from Hell Is a Right!,” “Good messes to be had from their catastrophism,” “What you need to know: Big System Collapse! Or not.”

More mess, good and bad: “Mess and reliability: five inter-related propositions,” “A different take on the traffic mess,” “Happiness: The mess,” “Who pays?,” “Misadventures by design,” “. . .and raise my taxes!,” “Top-of-the-list thinking,” “Take-home messages,” “Finding the good mess in supply and demand,” “The New Normal is managing not just negative setbacks but also positive ones,” “Good messes to be had from their catastrophism,” “Can’t we be best anticipatory and resilient at the same time?,” “The good mess in no single, right reading and in the many (more or less) wrong ones,” “Predicting the future”

Betterment and good-enough: “Betterment as ‘yes-but’ through ‘yes-and’,” “It’s better between the James brothers,” “Good-enoughs,” “Good-enough dreamers,” “Professional, amateur, apprentice; Or, As good as the fingernails of Manet,” “‘at sea,’ ‘from on high’,” “Betterment (continued),” “Better fastthinking in complex times,” “Humanism, by default,” “Good-enough criticism,” “When good-enough is better: a summary,” “What to do when policy articles keep ending where they should’ve started,” “Heuristics as clues”

Policy palimpsests and composite arguments: “Take home messages,” “Blur, Gerhard Richter, and failed states,” “Time as sinuous, space as interstitial: the example of total control,” “More on policy palimpsests: The European Union Emissions Trading Scheme, Scenes I and II,” “Shakespeare’s missing lines still matter,” “Bluejays, fists and W.R. Bion,” “Reflection and sensibility,” and other Longer Reads (below)

Economism: “Economism,” “Keep it simple?,” “Loose ends, #1” “When high reliability is not a trade-off,” “Short and not sweet,” “The missing drop of realism,” “The market failure economists don’t talk about: Recasting infrastructures and the economy,” “Finding the good mess in supply and demand,” “Makes the gorge rise”

Longer Reads: “Ammons and regulation,” “The next Constitutional Convention,” “Recalibrating Politics: the Kennedy White House dinner for André Malraux,” “Blur, Gerhard Richter, and failed states,” “A consultant’s diary,” “A different take on The Great Confinement,” “Market contagion, financial crises and a Girardian economics,” “New environmental narratives for these times (consolidated from Environment entries),” “New benchmark metrics for major risk and uncertainty (consolidated from entries for Risk, resilience and root causes),” “One ‘why’ and four ‘how’s’ to recasting complex policy and management problems (consolidated from earlier entries)”

Something less complex?: “Red in tooth and claw,” “What kdrama has taught me,” “The irony of it all,” “Dining on gin and consommé,” “Five questions everyone should want to answer,” “Distracted anti-utopians,” “Sallies out and sees,” “It’s as if,” “Proof-positive that international irrationality is socially constructed. . .”

Safety, like much in democracy and intelligence, is not a noun but an adverb

“Safety” is its most problematic when more a noun than as adverb. Safety, if it is anything, is found in practices-as-undertaken, i.e., “it’s operating safely.” If the behavior in question reflects a “safety culture,” that noun, culture, is performative and not something in addition to or prior to “culturally.”

Safety is no different from democracy or intelligence. They too act adverbially—“behaving democratically in that s/he, e.g., votes in elections, pays taxes and more”—and “thinks intelligently” (whatever that means in practice). To believe safety, democracy and intelligence are otherwise is like thinking you make fish from fish soup.

Narrative policy analysis, now and ahead


–Why would we ever think a book on policy written nearly three decades ago remains relevant? It seems to me that the major policy and management issues, though much changed, are still characterized by high uncertainty, complexity, incompletion, and conflict (polarization), the focus of the 1994 Narrative Policy Analysis.

So that we start on the same page, issues are uncertain when causal knowledge about them is found wanting by decisionmakers. Complex when their elements are more numerous, varied and interconnected. Incomplete, when efforts to address them are interrupted or left unfinished. And conflicted, when individuals take very different positions on them often precisely because of their uncertainty, complexity and incompleteness.

–Such issues are now grouped together as wicked problems said to be intractable to conventional policy and management intervention. In the older language, the “truth” of the matter is difficult if not impossible to establish—right now when a decision has to be taken.

If the truth can’t be established or is moot—i.e., there is no truth—what then are ways in which we can establish conditions to take a decision that claims urgency and priority?


In answer, though narrative analyses of policy issues have evolved over the three decades, two foci of the original approach remain salient. First its terminology and second, its drive to identify narratives that underwrite policymaking, given current intractability.

–First, the terminology. It’s next to impossible to avoid terms like policy narratives. They are those stories with beginnings, middles and ends, or if cast as arguments with premises and conclusions that policy types and managers tell themselves and others in order to take decisions and justify them.

The narrative analytical approach continues to ask you to start by identifying the different types of narratives in the issue of concern—some of which are very visible—the dominant policy narratives—others of which have to be found or identified, including marginalized counternarratives.

Assume you—the policy analyst, manager, researcher or decisionmaker—find a policy narrative to be too simplistic for the complexities at hand. You can rejigger that narrative in three ways: Denarrativize it; provide a counternarrative or counternarratives; and/or offer a metanarrative (or metanarratives) accommodating a range of story-lines (arguments), not least of which are versions of the simplistic narrative and preferred counternarrative(s).

  • First, denarrativize! To denarrativize is to critique the dominant policy narrative, point by key point. The best way to do that is to bring counter evidence to each point the offending narrative holds. To denarrativize is to take the story out of the story, i.e., to disassemble it by contravening its parts. Abundant case evidence exists to call into question the Tragedy of the Commons, for example.
  • First, counternarrativize! The chief limitation of denarrativization is the inability of critique on its own to generate an alternative narrative to replace the discreditable one. In contrast, a counter-story challenges the original by virtue of being a candidate to replace it. Common property resource management is said today to be the counternarrative to that older Tragedy of the Commons narrative.
  • First, metanarrativize! A metanarrative is that policy narrative—there is no guarantee there is one, or if so, only one—which the narrator holds in order to understand how multiple and opposing policy narratives are not only possible but consistent with each other. Claims to resource stewardship is a metanarrative shared by policies based in the Tragedy of the Commons as well as in other explanations, including but not limited to common property resource management. In this metanarrative, a group—the techno-managerial elite, “the community,” the Other—asserts stewardship over resources they do not own, because they alone, so the metanarrative goes, are capable of determining and adjudicating where and in what form better management holds.

–The second advantage of the original approach continues to be its recognition that decisions have to be made. Yes, of course, taking time to deliberate, being reflective and having second thoughts remain important, but even here acting these ways can end up being a decision of real import.

So, at some point you face a choice over which is the better policy narrative. For narrative policy analysis, a better policy narrative meets three criteria:

  • The narrative—its story with beginning, middle and end, or argument with premises and conclusions—is one that takes seriously that the policy or management issue is complex, uncertain, interrupted and/or polarized.
  • The narrative is one that also moves beyond critique of limitations and defects of the dominant policy narrative (criticisms on their own increase uncertainties when they offer no better storyline to follow).
  • The narrative gives an account that, while not dismissing or denying the issue’s difficulty, is more amenable or tractable to analysis, policymaking and/or management. Indeed, the issue’s very complexity—its numerous components, each varying in terms of its functions and connections—offers up opportunities to recast a problem differently and with it, potential options. Problems are wicked to the degree they have yet to be recast more tractably.

This means that the preferred policy narrative can be in the form of a counternarrative; or it can be in the form of metanarrative; but it won’t be in the form of a critique or other non-narratives like circular arguments or tautologies.

Nor should you think that in a planet of now 7+ billion people you have to invent a preferred policy narrative from scratch: Preferred policy narratives—note the plural—should be assumed from the get-go to exist and are being modified.

–To summarize, the policy narratives of interest for narrative policy analysis are not those used by policy types who insist they already know the truth. This approach is NOT about how various Big Lies have evolved from Goebbels through Trump, as in: The Jews were to blame before; the Blacks were to blame later; Islamists are to blame now.

Rather and to reiterate, the evolving field of narrative policy analysis over the last three decades remains relevant for those issues that policy types, analysts and researchers already admit a high degree of uncertainty, complexity, incompleteness and polarization—or again in today’s parlance the issues are wicked and intractable in their current casting.


–To see if we’re still on the same page by this point, assume in this simple thought experiment you are faced with two dominant environmental crisis narratives about globalization:

  • The green narrative assumes that we have already witnessed sufficient harm to the environment due to globalization and thus this narrative demands taking action now to restrain further global destruction. More research isn’t needed in order to decide that new action is required, now. This crisis scenario is certain in its knowledge about the causes and effects of globalization, in the view of many environmentalists.
  • The ecological narrative starts with the massive but largely unknown or uncertain effects of globalization on the most complex ecosystem there is, Planet Earth, now and going forward. More research isn’t needed in order to decide that new action is required, now. Here enormous uncertainties over the impacts of globalization, some of which could well be irreversible, are reason enough not to promote or tolerate further globalization, in the  view of many ecologists.

Both seek to stop harmful effects on the environment from globalization. But which is the better narrative when it comes to the next steps ahead in environmental policy and management?

Well, you know my answer. From a narrative analytical viewpoint, if future unpredictabilities—uncertainty, complexity, conflict and unfinished business—are taken seriously, the ecological narrative is the better one. Or if you are sure that in your case the green scenario is the one to start then and there, your challenge is to detail how conditions could lead to hitherto unspecified unpredictabilities in the local scenario(s).

Principal sources

Earlier blog entries: “Policy narratives,” “Better fastthinking for complex times”

E. Roe and M. van Eeten (2004). “Three—Not Two—Major Environmental Counternarratives to Globalization,” Global Environmental Politics 4(4).

It’s as if

. . .we came to Nietzsche because we loved his lieder;

. . .we know the murderer in Edwin Drood because Dickens told 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, having caused the first traffic jam on Broadway in New York City;

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

. . .a waterfall can’t be a commons;

. . .”it won’t happen here” is emergency preparedness;

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

. . .the only genuine political project is setting tax rates on the rich;

. . .everything is infinitesimal compared to a global GDP of some US$100 trillion;

. . .one does not come to the object after following the shadow;

. . .the people who question the use of GDP as a measure of health and the environment are the first to urge “Increase government budgets by x% of GDP for health and the environment and social protection 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;

. . .Andy Warhol’s work were a middle-brow modernism akin to 20th century bureaucracies;

. . .it wasn’t a bad day for practitioners when Nobel economists compared themselves to plumbers;

. . .poet Geoffrey Hill on Christian texts is not far more educating by being difficult than poet TS Eliot banging on about Christian theology;

. . .global climate change is World War III–only because the Cold War wasn’t:

. . .Walter Scott, having just learned of his bankruptcy, saying “No! This right hand shall work it all off!” is the same as the recanting Bishop Cranmer, thrusting out his hand into rising flames and saying, “This is the hand that hath offendeth. It shall be the first to burn!

Sallies out and sees

–I came across a quote of Teddy Roosevelt, US President: “In this life we get nothing save by effort; far better it is to dare mighty things; to win glorious triumphs, even though checkered by failure, than to rank with those poor spirits who neither enjoy much nor suffer much, because they live in the great twilight that knows neither victor nor defeat.”

Surely that paraphrases John Milton’s Areopagitica: “I cannot praise a fugitive and cloistered virtue unexercised and unbreathed, that never sallies out and sees her adversary, but slinks out of the race, where that immortal garland is to be run for, not without dust and heat”?

Why paraphrase, though? Just look at Milton’s verbs and adjectives: praise, fugitive, cloistered, unexercised, and those sallies and slinks. They’re descriptive and evaluative at the same time by way of provoking the reader.

–When it comes to social experiments, surely we experiment after having seen to it that others haven’t already developed better practices. As if it were unethical not to experiment in the face of urgency, when experimenting without having searched for better practices is itself unethical—and urgently so.

–In the mid-1970s a group of physicists and political scientists met at MIT and “arrived at the conclusion that if a World Government was not implemented soon, the probability of a nuclear war before the year 2000 would be close to 100 percent” But what were their nuclear war scenarios? Without details against which to evaluate, the experts are like the early astrologer who cast Christ’s horoscope and found the end of Christianity within sight.

–In the early years of World War I, Rainer Marie Rilke wrote that “the misery in which mankind has lived daily since the beginning of time cannot really be increased by any contingency. . . Always the whole of misery has been in use among men, as much as there is, a constant, just as there is a constant of happiness; only its distribution alters.” Here too is Jean-Paul Sartre, “essentially, there is not much difference between a catastrophe where 300 or 3000 die and one where ten or fifteen die. There is a difference in numbers of course, but in a sense, with each person who dies, so also does a world. The scandal is the same.”

Rilke and Sartre avoid a major point. The numbers do matter in determining whether or not misery is a constant in aggregate or individually. “From a statistical point of view, which is that of social and political life and of history, there is an enormous difference,” Maurice Merleau-Ponty said of Sartre’s remark. We know from survey research that conclusions are drawn much more confidently from structured surveys and samples consisting of 3000 people than, say, 30 persons. I may be misremembering, but I think it was Kenneth Boulding, the heterodox economist, who felt that the greatest contribution of the social sciences to humankind was the notion of the sample survey, as imperfect as it is.

–Voltaire, along with other Enlighteners, thought Christianity a useful distraction for the masses who could not cope with the rigors of reason. If I am right, the rigors of reason were just as useful for the Enlighteners in distracting them from the nonconscious origins of the superstitions they revolted against. The Enlightenment didn’t provoke the Counter-Enlightenment; the latter has been there throughout the evolution of the human brain’s more automatic and stereotypic thinking. “Being off track” may be “on track” in more complex ways than supposed.

–Stanley Cavell, a philosopher, wrote that “there is always a camera left out of the picture,” by which I take him to mean that were we able to bring the camera into its picture a very different picture results. So too for policy issues: The analyst who looks at an issue from a perspective late in his or her career is likely to see it differently than others earlier on.

A wonderful story of the poet, Donald Hall, illuminates how bringing the camera into its picture changes it. Archibald MacLeish told him about the actor, Richard Burton, and a brother of his:

Then Burton and Jenkins quarreled over Coleridge’s “Kubla Khan.” Jenkins said it was a bad poem: disgusting, awful. Burton praised it: magnificent, superb. Jenkins repeated that it was nothing at all, whereupon Burton commanded silence and spoke the whole poem, perfect from first syllable to last. MacLeish told me that Burton’s recitation was a great performance, and when he ended, drawing the last syllable out, the still air shook with the memory and mystery of this speaking. Then, into the silence, brother Jenkins spoke his word of critical reason: “See?

–I for one hope they throw wads of money at geo-engineering modelers, keeping them in front of their computer screens so as never to see the light of day. About as likely, though, as seeing a blue rose in the Sahara.

— Consider a passage from Virginia Woolf: 

Let us begin by clearing up the old confusion between the man who loves learning and the man who loves reading, and point out that there is no connection whatever between the two. A learned man is a sedentary, concentrated solitary enthusiast, who searches through books to discover some particular grain of truth upon which he has set his heart.  If the passion for reading conquers him, his gains dwindle and vanish between his fingers.  A reader, on the other hand, must check the desire for learning at the outset; if knowledge sticks to him well and good, but to go in pursuit of it, to read on a system, to become a specialist or an authority, is very apt to kill what it suits us to consider the more humane passion for pure and disinterested reading.

While claiming no connection whatever between learning and reading, her prose enables us to see one such connection, and an emphatically inverse one. 

–Start with T.S. Eliot’s lines from The Waste Land, “I can connect/nothing with nothing.” Note the ambiguity between “I can’t connect anything” and “What I can connect is nothing to nothing.” Now compare his lines to those of A.R. Ammons from his “Center:”

the noon sun casts
mesh refractions
on the stream's amber
and nothing at all gets,
nothing gets caught at all.

But you are caught up in reading this poem. Also, isn’t the shared “eye” of different readers meshed in there somewhere?

–Say you are on one of the upper floors of a skyscraper, looking out on the morning. That is Reality I: You are the observing subject looking out at reality. After a point, you realize that spot in the distance is actually a plane headed toward you, this morning in the World Trade Center. That is Reality II: You become the object of reality, in that grip of the real, and no longer just observer.

There is, however, Reality III. This is of the air traffic controllers during 9/11. Neither the observer of the first reality nor the object of second, these professionals achieved the unprecedented without incident that day. They were instructed to land all commercial and general aviation aircraft in the United States—some 4,500 aircraft—and did so. Without overdrawing the point, so too do we demand seeing that professionals land those water, electricity, transportation, telecommunications, and many more critical services every day without major incident.

When good enough is better: a summary

Calling something “good enough” borders on the pejorative in the US, as in “good enough for government work.” Less so, but still found wanting, is the sense in which a second-best result is good enough only because the optimal is not–yet??–achievable (think: efficiency benchmarks from microeconomics).

Here are the conditions under which good enough is better than said optima:

  • When it comes to complex policy issues, efforts at full or direct control to achieve results may produce effects well short of what would have been the case had one managed by adapting to the inevitable contingencies in trying to get there.
    • We of mid-twentieth century US were told that an annual economic growth rate of about 3% and an unemployment rate of about 4%, while in no way perfect, were good enough compared to the grief entailed in authoritarian measures to achieve substantially better.
    • Another way to say this is that good-enough improvisers using what’s at hand are better than macro-designers who see complete control as the best way to ensure better-than-“just” good enough.
  • Second, managing for good enough in processes that adapt to contingencies can produce results even better than the initial “best-case scenario.”
    • My examples include Anwar Sadat, Mikhail Gorbachev, and Nelson Mandela (or on a smaller, lesser known stage, Botswana’s Seretse Khama and Ketumile Masire). Each was a very imperfect person, comrade and leader, but each prevented some fresh hell on earth.
    • They were good enough to take us further than we could have expected, albeit we would want to go further still.
  • There’s also the sense in which a privileged “progress” or “growth” (economic, sustainable. . .) stops short of betterment, a really-existing good enough. They don’t take us far enough:
    • The key problem with insisting on progress or growth is that in doing so we can never be good enough today–better off today–by relying on yesterday’s standards.
    • But of course we can.

To ask, then, “Just how ‘good’ is good enough?” is to pose a systematically misleading question. “You must respond within x minutes of a call. . .” risks goal displacement, where meeting the criteria becomes the end in itself. But good enough isn’t assured once and for all. Indeed that’s the whole point: Good enough can, in its indefiniteness, last longer than progress or growth.

Principal sources: See more detailed blog entries, “Betterment as ‘yes-but’ through ‘yes-and’,” “Good-enoughs,” “Good-enough dreamers,” and “Betterment (continued)”