[In a first for this blog, this post is co-authored with my colleague Rob Johnston, Director of the George Perkins Marsh Institute and Professor of Economics at Clark University. I’m grateful for his willingness to work with me on this]

A recent blog post by NYU marketing professor Scott Galloway has been making the rounds recently, not only via his twitter feed and extensive mailing list, but also as a column in Business Weekly and the source material for articles in media outlets like MassLive (we’re not providing links because, as will become clear, we don’t want to reward this work with clicks). Ostensibly a post on the risk Covid-19 presents for higher education, this work is best characterized as pseudo-science designed to generate splashy media headlines. Nothing generates clicks quite like existential doom, and in this sense, both Galloway and media outlets win with content like this. If you are into marketing, and you subscribe to the maxim “there’s no such thing as bad publicity,” this is an interesting case study. Look closer, however, and it becomes obvious that this is much ado about nothing—Galloway’s study is simply unverified and unvalidated speculations that appear driven by his particular view of fragility in higher ed. 

It’s unfortunate that media attention which might have gone to meaningful research on the pandemic was instead devoted to a blog post such as this one. We would rather not validate the “eyeballs at all costs” approach behind Galloway’s post and therefore give him more of the attention he so clearly desires. However, the media stories that have emerged from his analysis have cast the well-being of our institution, and several others, into question. We, and we suspect others across higher ed, are hearing expressions of concern from students, parents, and alumni. It is therefore important to demonstrate that the analysis in question is appallingly bad (analogous analysis would not receive a passing grade in either of our classes), why this is the case, and why nobody should take it seriously.

While there are many ways to challenge Galloway’s “analysis” (scare quotes are the only way to dignify this work with that term), we focus on three categories of problem. First, there are flaws with the data used and its connection to the conclusions he attempts to draw. Second, for an analysis that is supposedly centered on Covid-19 risk, there is nothing in it that reflects the different epidemiological situations of institutions around the United States. Third and most importantly, this “analysis” is not anchored in any empirical testing or validation, though it easily could be. As a result, it is entirely self-referential and open to manipulation to provide any result desired by the author (or anyone else), including clickbait narratives of doom.

First, the data. The data Galloway employed was what he could find easily, as opposed to the data he needed to create a valid and reliable analysis. While all analyses are constrained by the data at hand, this appears to be a particularly lazy case of the streetlight effect. As a result, the data chosen for this analysis are entirely ad hoc and lacking in clear links to actual institutional outcomes (e.g., whether institutions have failed in the past or are failing now). Their predictive value is unknown. Some examples of the data issues that pervade this analysis:

  • Galloway’s analysis attempts to tie the value of an institutional credential to the institution’s average monthly online search volume. Whether this is valid in any context is debatable, but even if we accept this premise there are many things that distort that volume. Power Five conference schools have substantially higher search volumes than smaller universities and liberal arts colleges because they have nationally-ranked football teams and are often home to more than ten times the undergrads, not necessarily because people think those degrees are higher value. There is no evidence that Galloway attempted any sort of normalization for these effects before simply linking search volume to brand value (which seems ironic for a marketing professor).
  • It appears that this analysis treats higher instructional wages per full-time student as a good thing without explaining why. Salaries are shaped by a range of factors, including regional markets and the composition of the institution (institutions with law schools, medical schools, and engineering schools will have much higher instructional wages than those without). Again, without an effort to address these differences, the crude application of salary to institutional quality is rendered somewhere between problematic and meaningless.

Looking across the data he employs, Galloway doesn’t seem to understand what he is comparing when he looks across institutions, or the underlying financial situations of those institutions. For example:

  • The analysis makes no distinction between all-undergrad institutions and institutions with graduate and professional programs, despite the fact that these institutions have very different sources of reputation and revenue. These distinctions produce very different opportunities and challenges across these institutions. Indeed, enrollments in graduate professional programs are in some ways countercyclical to undergraduate admissions, offering financial hedges to institutions that house them. This seems to be one of many critical oversights in this analysis.
  • Incredibly, the analysis makes no distinction between state institutions and private institutions, which for reasons of revenue and politics will have very different fragilities and pathways to success.

Second, we note that for a piece purported to be an analysis of the risks Covid-19 poses to the health of institutions of higher ed, this work displays a shocking lack of data that measure Covid-19 risks or impacts. The actual rates of infection, stress on local and regional health systems, and the likely future trends in both are critical indicators for such an analysis. So too are the different guidelines that are in place for institutions in different states, or the different procedures that institutions might (or might not) be taking to attenuate risks. This sort of data speaks to the likelihood of different institutions having to close all face-to-face instruction, or even to close completely for a term or more. None of this information is in Galloway’s analysis, despite its wide availability on a range of platforms. Instead, Galloway assumes an oddly even risk across the United States at a time when extraordinarily clear regional discrepancies are emerging.

Third, this ad hoc “analysis” is self-referential: there is no attempt to validate it empirically. Galloway might have taken his proposed index and applied it to schools that have closed in the past year, or perhaps applied it to those that have closed over the past decade (as Covid-19 is largely cast as a stressor exacerbating existing issues for institutions) to check its explanatory power. This is standard practice in modeling exercises, used both to tune models and to assess their validity.

Instead, a range of critical questions go unanswered. Are appropriate variables included in the index? Are these variables weighted in the right way?  Without careful validation against real data (e.g., whether institutions have thrived, perished, etc., or are doing so now), one cannot determine whether the proposed index has any predictive validity whatsoever.

Without testing, the implicit model behind this analysis is self-referential and easily engineered to produce any desired outcome. Do the results support the position you want to advocate? If not, just remove a variable or two, substitute new variables, or change the weighting (importance) given to different variables. Eventually you can get an analysis that tells a story that you like – even if that story is detached from reality. Because Galloway’s analysis has not been validated or ground-truthed in any way, there is no way to determine whether it tells us anything useful. 

This is not research. This is embarrassing and irresponsible. Perhaps even more disappointing, shoddy “analysis” of this type threatens to erode the long-term confidence that the public and policy-makers have in all research—including careful research that applies valid, reliable and peer-reviewed methods. In his original blog post, Galloway used an aside that his analysis has not been peer reviewed and a weak admonition that he sees this work as starting a conversation (at which, of course, he is the center) as a fig leaf to excuse this shoddy, irresponsible work. We view this as an astonishing abdication of responsibility by a person with a large audience who had to know his half-baked “analysis” would create significant concern at a number of institutions. As academics, we see his stipulation as an acknowledgement that this analysis is so poor that there is no chance that it would survive peer review, or indeed be recoverable with revisions in a manner that would make it so. Bluntly, this analysis is so problematic and badly flawed that institutions it has slated to “thrive” or “survive” should perhaps consider their own situations carefully before feeling good about how they were characterized here.

This is not to say that Covid-19 poses no challenge to higher education, or even to suggest that higher education might not benefit from some reflection about its goals and practices at this time. We welcome careful research to address these important issues. However, we feel that identifying and addressing such challenges requires serious research and analysis, not the headline-grabbing dumpster fire that lurks beneath Galloway’s post and the resultant media attention.

If something useful can come of this absurd offering, it is to demonstrate the value of higher education when well-executed. We feel quite confident that any good undergraduate at Clark, and certainly all of our graduate students, would have received the training in critical thinking, research, and analysis necessary not only to identify many, if not all, of the problems we point to here, but to conduct such an analysis in a more effective, productive manner. 

In the New England I knew as a child, people commonly paraphrased Mark Twain’s famous line “If you don’t like the weather in New England now, just wait a few minutes.” This was true year-round, but when it comes to rapidly changing temperatures, winter really had its moments. Most years, there seemed to be a day in the middle of January when the usual freezing days would give way to one that reached 50 or 60 degrees F. This prompted everyone to go outside in shorts before returning to the layers of winter for another three months. Why everyone had shorts at hand in the middle of January in New England is a regional mystery that remains unexplained.

When it comes to temperature, New England has always been a pretty variable place. When I moved back, I assumed it still would be. But after returning and living in the region for a year, that variability started to feel odd. For example, I became acutely aware of the surprising number of December days that reached the high 40s or low 50s, mostly because there is no indoor track in Worcester so I train outdoors all year (a note to the city of Worcester: Seriously? Nine colleges and lord-knows-how-many high schools, all looking for somewhere to train and race, and nobody thought to build an indoor track? 1). While the temperature is still marked by significant and relatively rapid changes, these temperature swings seem more drawn out than I remember. Where my understanding of variable temperatures was formed around a world marked by a day or two of outlying conditions followed by a return to expected temperatures, in 2017 October averaged 57 degrees Fahrenheit for the month, wildly out of line with even the 2010-present average of 52.

NOAA defines extreme temperatures as falling in the upper 10th percentile (for warm temps) or lowest 10th percentile (cold temps) across the time for which records were kept. In terms of heat, the figure below shows the percentage of days where the daytime high meets this definition of extreme. It is important to note that in the chart these extremes are relative to the month in question. In December, an extreme high is a temperature above 51.1 F, while in July it is above 87.1 F. Both are significant deviations from the norm, but the human experience of each is quite different.

In fact, the number of days marked by extreme/unusual high temperatures, just under 43 per year, has not changed since my childhood. However, as the chart shows, the distribution of these extremes throughout the year has changed. September has seen the greatest increase in these unusually hot days, which contributes to the sense of a longer summer season. On the other hand, the average number of days with extreme high temperatures in January and February has not changed much. We still have unusually warm periods in those months, but their frequency and duration is similar to that I knew as a child. March, June, and August are marked by fewer such days.

There has been a more dramatic change in the patterns related to extreme cold days – annually, there are now 26 fewer unusually cold days than seen in my childhood. This decline is visible in every month. August has more than three fewer unusually cold days, a change that means that today we see one such a day every five years. Along with overall increased average temperatures, and a longer duration and larger number of increased temperatures, this makes for a summer that feels more consistently summery.

There are four fewer extremely cold days in December, and these days now occur less than once a year. This is both a staggering change, but also a marker of a past that is now gone. Part of my identity is based on my ability to shrug off really cold temperatures, an ability borne of being sent outside to play regardless of the temperature throughout my childhood. Who from my generation did not make the mistake of coming inside, using the bathroom, and washing their hands under hot water too soon? If you have not done this, it really shocks the nerves and feels like someone is jamming dozens of needles into your hands. Generally, you make this mistake once. My kids are big Star Wars fans, but unless they concentrate on outdoor play during February, the warming temperatures mean they will probably not be reenacting versions of the Hoth scene from Empire Strikes Back as frequently as I did with my friends, and probably complain more when it is cold.

In my head, this image of my childhood home is still what winter should look like

The wild swings in temperature I recall from my childhood also appear to have become less frequent. There is a reason most New Englanders my age or older have an innate sense of layering in their wardrobes. That said, there’s also something very New Hampshire about a nostalgia for the days when you’d start sweating in your snowsuit because you needed it when you first went out, but it had since warmed up into the 50s while you were outside.

“Hey kid, if you’re big enough to sled, you’re big enough to help shovel the driveway!”

To better understand this change, I looked for days where the high temperature either increased or decreased by 20F or more from the day before. The charts below show what I found – overall, it appears that we see fewer of these swings now than in the past.

Where once there was an average of about 18 days per year where the temperature was 20 F warmer or cooler than the day before, today there are fewer than 13 days. As with most other temperature-related conditions, the deep winter period of January and February is much as it was in my childhood. Nearly every other part of the year has changed. For example, it appears the swings in temperature that I used to associate with March are being displaced into April and May. While July, August, and September rarely saw such swings in the past, they have now disappeared completely. Again, summer is becoming more consistently summery. Where November and December were once ground zero for this sort of day-to-day temperature change, today the temperature in these months has become more stable than in the period from January through April. Those warm days in December reflect high temperatures relative to my memory, but it doesn’t get as cold in December as it used to. Those temperatures feel unusually warm to me, but relative to current conditions they simply don’t qualify as extreme.

Once upon a time, you had to pack sweaters and jeans for a Salsbury beach vacation because even in early August you were going to get one of those days…

Even contemporary daily temperature changes are less pronounced than in my childhood. The chart below shows that the average day now operates in a somewhat smaller temperature window than in the past – across the year, the difference between the daily average high temperature and the average low temperature has shrunk by 1.3 degrees Fahrenheit since I was a child. This trend is true in every month, but very pronounced in October and December. Most of this change can be attributed to the fact that daily average low temperatures are rising faster than daily average high temperatures.

Taken together, this evidence suggests that, at least when it comes to temperature, the New England of “if you don’t like the weather, wait a minute” is going away. Since my childhood the weather has become a bit more predictable and a lot warmer. For a guy who prided himself on his resilience in the face of very cold and rapidly changing weather conditions, a resilience borne from a childhood outdoors in New England, this feels sad. It also challenges an identity I’ve carried throughout my adult life, which I lived almost entirely outside New England. I lived mostly in more temperate (if not tropical) climates. In those places I enjoyed being the New Englander, relatively unbothered by swings in temperature that made those around me complain. I took some pride in the ways in which my childhood had inured me to such discomforts. But now New England is warmer and, let’s be honest, just a little more boring when it comes to temperatures. My children are unlikely to develop quite the same sense of identity. Then again, this might be for the best. Compared to their father, they’ll be less insufferable when confronting cold or highly variable weather alongside those from warmer climates.


  1. If you happen to have some capital laying around and are into track, I can help you spend it in Worcester – you are sure to make a mint, and I can stop freezing my ass off while trying to work out in January

As my previous post suggested, since returning to New England after 24 years away I have found the relationship between temperatures and seasons oddly dislocating. The previous post explored how summer temperatures have changed since my childhood, and why I am experiencing them the way I am. In this post, I look at changes to fall and winter in Worcester. This post not only explains what is happening to winter in this part of New England, but also fleshes out something remarkable: the annual structure of temperature in this part of the world has changed in profound ways since my childhood. Where I grew up in a world where wintery temperatures lasted much longer than those of summer, today winter and summer temperatures are nearing parity on an annual basis. Fall transitions into winter much later than when I was a child, but winter ends only a little earlier than it used to. At least when it comes to temperature, Worcester (and New England more broadly) is a very different place than the one in which I grew up.

Let’s talk about fall. Since returning to New England, I have found this season particularly disorienting. I expect it to become cold much sooner than it does, and find myself increasingly unsettled by the temperature across October, November, and December. I have clear memories of a much colder fall, and a much harsher transition to winter, than what I experience now. On November 12, 1990, my high school soccer team won the NH state championship on a frozen pitch in 27-degree Fahrenheit weather (it was 23 degrees Fahrenheit that night in Worcester) 1. I’m not crazy in coming back to that memory. During my childhood, the average high temperature on November 12th was 44.5 degrees Fahrenheit, with average lows of 30.9, so that game was a slight outlier. Today, that average is 51.5 degrees Fahrenheit, with average nighttime lows of 33.2…which would make that game a larger outlier, but also as that average nighttime low is above freezing, it also means that a frozen pitch would be a very unusual event. Further, the onset of winter temperatures, signaled by the first hard frost, has changed. The first hard frost now comes an average of 16 days later than when I was a child (previously October 24th, now November 9th). In other words, even if the game is played on a freakishly cold night, it is unlikely that soccer players in NH will have to play 2 a State Championship game on a frozen pitch again.

If I feel bit adrift in the fall and early winter, I tend to come into port in January, February, and March. This is despite the fact the data suggest that the change in winter is even more striking than that in fall. The period characterized by hard frost, between the date temperatures first drop to 28 Fahrenheit or lower and the last day temperatures reach this point, lasted an average of 173 days each year during my childhood. Today, the average for this period is 148 days, a mind-boggling 25 days shorter. The figure below compares the period of winter temperatures, as marked by the first and last hard frost, across the year as it was when I was growing up and today. As noted above, today the first hard frost is delayed by more than two weeks relative to my childhood. The last hard frost arrives nine days earlier in the year (previously April 16th, now April 7th).

The distribution of winter weather across the year in my childhood and today. The graphic shows how the winter ends earlier, and starts later, than it used to.

Why, then, would I feel most at home in the temperature in January, February, and March? The answer also lies in the data: once we get past December, the temperatures within winter start to converge with the temperatures I knew growing up. We used to average 113 days per year that reached 28 Fahrenheit or lower. Now the average is 93 days, an incredible decline of 20 days in just over 25 years. However, the relative proportion of total days below 28 Fahrenheit in winter has not changed much. When I was growing up, an average of 65% percent of winter days reached temperatures below 28F. Today, that average is 63%. Most of those days are concentrated in January and February. The average temperature in the month of January might be 2.53 degrees Fahrenheit warmer than what I grew up with, but it is still only 25.2 degrees! Similarly, while February is also warmer (by 1.41 degrees Fahrenheit), the average temperature is 27.5 degrees Fahrenheit, still below the hard frost temperature. Today, March is actually colder than in my childhood, though only by .14 degrees. All of this means that these months feel quite similar to those I experienced as a child.

It’s the transitional seasons in and out of winter (particularly fall), the margins of the winter itself, that have seen the greatest changes. The transition to spring, however, is gentler on me than Fall. April, while today an average of 1.21 degrees Fahrenheit warmer than in my childhood, has not radically departed that past experience. The spring in New England is still long, still muddy, and still unpredictable. After April, May warms up considerably, and we are into my earlier discussion of changes in summer.

People, like plants and other animals, have a degree of photosensitivity – an expectation of what things should feel like temperature-wise at a given length of day and angle of the sun. Nothing has changed with regard to the length of day or the angle of the sun, but for much of the year the temperature in New England no longer aligns with these other factors in a manner I understand. The chart below captures these changes across the year, illustrating how the character of daily temperatures in New England has changed enough to render this place nearly unrecognizable.

What it shows is that while nearly every month has seen some temperature increase, every month has seen an increase in the average minimum temperature, and that increase is larger than the increase in average high temperature. Put another way, the difference between daytime and nighttime temperatures is compressing, whether gently as in April, or dramatically, as in October and December. The connection between hours of sunlight, the angle of the sun, and temperature that I developed for myself playing in the woods behind my house in the 1970s and 1980s is an artifact of an environment that no longer exists. For someone to understand what I am talking about in a visceral way, they have to be around my age (or older), and to have spent enough time outdoors in daylight to have developed this sense.

The figure below visually represents the radical change in the structure of temperatures across the year since my childhood. It is a to-scale representation of the average duration of the “hard frost” and “summery” 3 temperature periods, both when I was growing up and now. The intervals between the seasons are also to scale. It shows that in the space of the past 25 years, where I live has gone from a winter-dominated temperature signature to one approaching parity between winter and summer temperatures. When I was growing up, wintery temperatures lasted an average of 52 days longer than summery temperatures each year. Today, wintery temperatures only last 13 days longer than summery temperatures. The shift is staggering, and explains my general dislocation when it comes to temperature, particularly in the fall.

Summer and winter temperatures laid out across an annual scale. The shift toward annual parity between summer and winter is clear.

One thing is clear: my children are growing up with a very different sense of the relationship between the amount of sunlight, its angle, and temperature than I did. They live in a different world than the one in which I grew up. Another thing is sure: given the inertia in our climate, my children will have some version of the experience I am describing at some point in their own lives. I worry, however, that they will not get to their mid-40s before this awareness sets in. Rates of change are not slowing, and there is little to suggest that we will stabilize global temperatures (a prerequisite to stabilizing local temperatures) in their lifetimes. I’ve lost a connection to the world that I loved, and I will not get it back. I was gone too long to make the subtle adjustments to my perceptions necessary to overlook this change, and after four years I still feel dislocated every fall. The terrible part of this is that we’ve already ensured that our children will have this same experience. The question is not if, but when.


  1. Yes, I had to look the date up. I had no memory of that the game being on a Monday night
  2. The key term is play, which I use advisedly here, as I was a reserve striker on that team and never got into that game. It’s not fun to watch a championship game from the bench. It’s worse when you are freezing
  3. Recall from my previous post that I am defining “summer-like” somewhat arbitrarily as the period between by the first day of the year over 25 Celsius (77 Fahrenheit) that was followed by consecutive days of temperatures above 70 degrees and closed by the last day over 25 Celsius at the end of several consecutive days over 70 degrees

Resilience is a term that permeates development and adaptation conversations alike. However, it is often used without clear definition, and the definitions assumed or elaborated generally misrepresent the dynamics of human-dominated systems.

TL;DR: We’re doing resilience wrong, and it is screwing up the lives of people who are supposed to benefit from resilience programming.

To address this problem, I recently wrote an article seeking to address these conceptual issues and make resilience a useful, constructive concept for development and adaption. The key points:

  • Socio-ecological resilience is an outcome of projects steering diverse actors and ecological processes toward human safety and stability in a manner that preserves the privileges of those in positions of authority.
  • At even moderate levels, disturbance in socio-ecologies is not a source of transformation, but instead produces rigidity that limits innovation and transformation in the name of safety and stability. When a resilient system provides safety in the context of a disturbance, the system and its attendant social orders and privileges are legitimized. This is why many development projects fail: they gently disturb a project, which rejects the intervention in the name of safety and certainty, and returns people and activities to their initial state.
  • Disrupting resilient socio-ecological projects, whether through extreme disturbance or interventions associated with development and adaptation, opens space for transformation, but creates risk by removing existing sources of safety and certainty. This is another source of project failure, one where the intervention blows up the existing project, but what comes together in its wake leaves some or all of the people involved more vulnerable to existing stresses, or vulnerable to new stresses that leave them worse off than they were before the intervention.
  • Reinforcing existing socio-ecological projects, such as through interventions aimed at stabilizing existing activities, reduces opportunities for transformation by legitimizing their practices and social orders.
  • Interventions seeking to build resilience while achieving transformative goals can catalyze change by easing stress on livelihoods. In the context of reduced stress, the side of these projects aimed at maintaining existing structures of authority relaxes, allowing space for innovations by actors who are otherwise marginal to decision-making.

There is a lot going on in this article, and I intended it as much as a provocation as a path forward. If any of this is interesting or challenges the way you saw resilience in the world, feel free to read more deeply – the article is here.

Unsolicited publishing advice/reviewing rant to follow. Brace yourselves.

When writing an article based on the quantitative analysis of a phenomena, whatever it may be and however novel your analysis, you are not absolved from reading/understanding the conceptual literature (however qualitative) addressing that phenomena. Sure, you might be using a larger dataset than ever used before. Certainly, the previous literature might have been case-study based, and therefore difficult to generalize. But that doesn’t give you a pass to just ignore that existing literature.

  • That literature establishes the meanings of the concepts you are measuring/testing
  • That literature captures the current state of knowledge on those concepts
  • Often, that literature (if qualitative, especially if ethnographic) can get at explanations for the phenomena that cannot be had through qualitative methods alone

If you ignore this literature:

  • You’ll just ask questions that have already been answered. Everybody hates that, especially time-constrained reviewers who already know the answers to your questions because they actually have read/contributed to the literature you ignored.
  • You’ll likely end up with results that don’t make sense, and with no means of explaining or even addressing them. Editors and reviewers hate that, too.
  • Your results, even if they appear to be statistically significant, will be crap. I don’t care how sophisticated your quantitative analysis is, or how innovative your tools might be, you are shoving crap into a very innovative, sophisticated tool, which means that all you’ll get out the other end is crap. Reviewers hate crap. Editors hate crap. And your crap is probably not actionable (and really shouldn’t be), so nobody outside academia will like your crap.

Please don’t generate more crap. There is plenty around.

Finally, a note on professionalism and your career: Citing around people who have worked on the phenomena you are investigating because you are trying to capture a particular field of knowledge is awful intellectual practice that, beyond needlessly slowing the pace of innovation in the field in question, will never work…because editors will send the people you are not citing the article for review. And they will wreck you.

Back in September, HURDL released its final report on our work assessing Mali’s Agrometeorological Advisory program – an effort, conceived and run by the Government of Mali, to deliver weather and climate information to farmers to improve agricultural outcomes in the country. You’d think this would be a straightforwardly good idea – you know, more information (or indeed any information) being better than none. So our findings were a bit stunning:

  • As we found in our preliminary report, less than 20% of those with access to the advisories are actually using them
  • Nearly everyone using the advisories is a man
  • Nearly everyone using the advisories is already relatively well-off
  • The advisories were most used in the parts of the country where precipitation is most secure (see map below).

Screen Shot 2016-01-17 at 5.10.27 PM

This was, to say the least, a set of surprising findings. And, on their surface, they suggest that the program is another example of development failure: a project that only reaches those who least need the help it is providing.

But that conclusion only holds if this program was oriented toward development and adaptation in the first place…and it was not. The program was established in 1981 as an effort to address conditions of acute food insecurity closely linked to severe drought. The goal was simple: use short-term and seasonal advisories to help farmers make better decisions under stress and boost food availability in Mali. This program, in other words, was an effort to address a particular, acute problem (food insecurity linked to extreme drought) through a very specific means (boosting food availability). This was not a development project, it was a humanitarian response to a crisis. And as such, it was brilliant – and each of the findings above demonstrate why.

  • The goal was to rapidly boost yields of grains (and cotton), for which men have most decision-making authority.
  • The goal was to rapidly boost overall yields of grains to improve availability within Mali, and therefore targeting the wealthy farmers who had the access to equipment and animal traction necessary to use the advisories made sense.
  • The goal was to rapidly boost grain production…and much more grain is grown in the wetter parts of Mali than in the dryer areas in the north.

In short, the project was never intended to address development goals – it was supposed to address a particular aspect of a humanitarian crisis through particular means, and its design targeted exactly the right decision-makers/actors to achieve that goal. Indeed, one could argue that the rather narrow use of advisories speaks to how well designed this humanitarian intervention was. In short, the gendered/wealth-dependent character of advisory use, and the fact they are most used in areas that are already very agriculturally productive, are not bugs in this project: they are features!

The problem, then, is not with the design of the project, but the fact it continued for more than 30 years, and some 25 years after the end of the droughts. As a narrowly-focused effort to address a particular, short-term humanitarian crisis, the gendered/wealth-based outcomes of the project were acceptable trade-offs to achieve higher grain yields. But over 30 years, and without the justification of an acute crisis, it is likely this project has served to unnecessarily exacerbate agricultural inequality in rural southern Mali.

HURDL is now engaged in a project to redesign this program, to shift it from a (now unnecessary) humanitarian assistance effort to a development/adaptation project. With this shift in priorities comes a shift in how we view the outcomes of the program – the very things that made it an effective humanitarian assistance program (gendered and income-based inequality) are now aspects of the project that we must change to ensure that the widest number of farmers possible have access to information they can use in their livelihoods decisions as we move into conditions of greater economic and environmental uncertainty. In short, we now have to bridge the DRR and Humanitarian Response/Development and Adaptation divide that has so plagued those of us concerned with the situation of those in the Global South. This will be tremendously challenging, but through this process we hope to not only work with Malian colleagues to design and deliver a development and adaptation version of this program to Malian farmers, but also to learn more about how to bridge the particular time/scope emphases of these two assistance arenas.

Last week, I published a short editorial in Scientific American’s SA Forum online that decried the near-total lack of organization or prioritization in the Sustainable Development Goals/Global Goals/whatever they are called this week. My argument was simple: by not ordering or prioritizing goals, the SDGs

risk becoming an empty exercise that empowers business as usual in the field of global development.

At the conclusion of that piece, I suggested that the only way to avoid this outcome was to find actors who were able to demand organization and prioritization among these goals – principally the big bilateral donors like USAID and DfID, or perhaps the Gates foundation (which, on expenditures, comes in around the world’s sixth-largest donor organization).

I’ve been taken to task a few times by colleagues for this suggestion. These rather polite and professional interventions (I know, not at all like the internet I’ve come to expect) pointed out that I’d empowered the big donors, with their problematic, often Eurocentric framings of development and how to achieve it, to act as the saviors of development via the SDGs. Given my rather clear critical stance with regard to these framings of development (most clearly articulated in Delivering Development, but generally present in most of the stuff I write), I think some folks were mystified by my logic. So allow me to clarify:

When we refuse to define terms, organize concepts or efforts, or engage in the politics necessary to set priorities, we are not apolitical: we are empowering other political agendas. The basic argument of my op-ed was simple: by not making hard decisions, we have empowered a particular political agenda, one that leaves development in a business-as-usual situation. Therefore, I see nearly any effort at locking down priorities and organizing efforts as superior to no prioritization at all, because any effort to set priorities will accomplish two things:

First, it will bring politics to the fore, and we will all be forced to wrestle with what we want to prioritize and why.

Second, it will lock down the meanings of the different terms we use (i.e. sustainable, well-being, secure) in such a way that they can become sites where politics can happen.

What do I mean by this? If, as we have done to this point, we refuse to define what we mean by sustainable (for example), we create a conceptual container that can be filled by nearly any definition, policy, program, project, or activity. It allows completely contradictory efforts to coexist and cancel each other out, without providing a base from which to contest any or all of these efforts. When there are no definitions, everything using a given term can be seen as equally valid. Similarly, if we refuse to prioritize our efforts, organizations can fill their efforts to meet the SDGs with almost any hodgepodge of policies, programs, projects, or activities…and will likely do so in a manner that mirrors their current emphases, funding, and staffing structures. Thus, organizations could set up completely contradictory agendas, with associated material efforts, and be seen as making equally valid efforts to address the SDGs in the eyes of the donors and the public. There is no way to contest the way one organization or another does its business if there are no definitions or priorities from which to work.

This does not mean that I think any particular donor organization will save the SDGs by setting the agenda we need to move forward. All are mired in their own internal and/or national politics, and therefore will push for agendas that most clearly reflect their own strengths and priorities. Further, most donor organizations do, in fact, operate from rather problematic, Eurocentric framings of the world, for example in their continuing inability to recognize the genius of small farmers who already negotiate uncertain environments and economies. As I have written about at length, in the eyes of most donor organizations these farmers are poor and helpless in the face of these large forces, and in need of help/saving/education. As a result, the donors cannot identify the things that these farmers really need (which are often a lot more narrow than a total reworking of their agricultural systems) and, even worse, they cannot learn from the things these farmers already know about how to best manage their agricultural, economic, and social environments.

So no, I don’t think the donors will save us…directly. But if one or more are willing to step up and impose politics on this process, they will create a process by which terms gain definition, and efforts are prioritized. When these meanings become fixed, it becomes possible to engage them and contest them, to actually have a conversation about what development is, and what it should be. Right now, we can just hold hands, say words like sustainability, and watch a nice concert together, all the while operating under the illusion that we have the same goals, and that we are working toward those goals in the same ways. That gets us nowhere. I want a development world where we are forced to recognize that different organizations and individuals prioritize different things, have different visions of the future, and different means of moving us toward those visions. Further, I want a development world where we have to struggle with the fact that what organizations want may have little to do with what the global poor want. That is what the SDGs could have given us.

It is too late to make the SDGs’ 17 goals and 169 targets a site of real development politics. But all is not lost: over one thousand initiatives have been set up to meet these targets and achieve these goals, and many more are coming. This is where the goals will become impacts on the ground. If we can create a real politics of development around these initiatives by organizing and prioritizing them, perhaps we can recover the SDGs as a site from which we can build a truly transformative agenda for development.


So, I have news. In August, I will become a Full Professor and Director of the Department of International Development, Community, and Environment at Clark University. It is an honor to be asked to lead a program with such a rich history, at such an exciting time for both it and the larger Clark community. The program uniquely links the various aspects of my research identity within a single department, and further supports those interests through the work of a fantastic Graduate School of Geography, the George Perkins Marsh Institute, and the Graduate School of Management. At a deeply personal level, this also marks a homecoming for me – I grew up in New Hampshire, in a town an hour’s drive from Worcester. My mother is still there, and many friends are still in the region. In short, this was a convergence of factors that was completely unique, and in the end I simply could not pass on this opportunity.

This, of course, means that after twelve years, I will be leaving the University of South Carolina. This was a very difficult decision – there was no push factor that led me to consider the Clark opportunity. Indeed, I was not looking for another job – this one found me. I owe a great deal to USC, the Department of Geography, and the Walker Institute for International and Area Studies. They gave me resources, mentoring, space, networks, support, etc., all of which were integral in building my career. Without two Walker Institute small grants, the fieldwork in 2004 and 2005 that led to so many publications, including Delivering Development, would never have happened. The department facilitated my time at USAID, and the subsequent creation of HURDL. I will always owe a debt to South Carolina and my colleagues here, and I leave a robust institution that is headed in exciting directions.

As I move, so moves HURDL. The lab will take up residence in the Marsh Institute at Clark some time in late summer, assuming my fantastic research associate Sheila Onzere does not finally lose her mind dealing with all of the things I throw at her. But if Sheila is sane, we’ll be open for business and looking for more opportunities and partners very soon!

I’ve been writing here on Open the Echo Chamber since July of 2010. Good lord, that is a long time. I’ve cranked out well over 250,000 words on the site (plus or minus 30 articles, or about three books, worth of writing). And for all of that effort, I have received exactly no credit at all for this in my academic job. In my annual reviews and promotion packets, I can shove this work under “service”, but 1) most of my colleagues probably wouldn’t agree with that categorization and 2) nobody in academia gets much of anything for their service contributions unless they are a full-on administrator. I don’t blog for my academic career, I blog as a means of getting ideas outside the rigidity of the peer-review publishing world, the ways it gates off knowledge from those that might use it, and the ways it can police away innovative new thought that challenges existing powers. So, when I recently stumbled across The Winnower, I got excited. “Publish my posts with review and a DOI?” I thought. “Make my posts citable in major journals and technical reports?” I chortled. “Further blur the lines between my academic publishing and the stuff I do on this blog?” I fairly giggled. Yeah, I need to give this a try.

Let me explain:

According to the lovely people at Google Analytics, in that time nearly 50,000 users have committed to over 100,000 pageviews. For a blog that is home to some long, wonky posts, that is pretty amazing. Readership comes from all over the world, with the top 10 countries looking like this:

  1. United States 37,530(52.18%)
  2. United Kingdom 7,990(11.11%)
  3. Canada 4,186(5.82%)
  4. Australia 1,949(2.71%)
  5. India 1,339(1.86%)
  6. Germany 1,019(1.42%)
  7. Netherlands 834(1.16%)
  8. Kenya 773(1.07%)
  9. Philippines 722 (1.00%)
  10. France 695 (.97%)

It is remarkable that Google lists visitors from 192 different countries and territories. And when you drill down to cities, it gets pretty cool as well:

  1. Washington 5,023(6.98%)
  2. London 3,419(4.75%)
  3. New York 2,965(4.12%)
  4. Columbia 2,326(3.23%)
  5. Irmo 1,273(1.77%)
  6. Toronto 769(1.07%)
  7. Seattle 713(0.99%)
  8. Fonthill 676(0.94%)
  9. Melbourne 642(0.89%)
  10. Nairobi 604(0.84%)
  11. Sydney 532(0.74%)
  12. Cambridge MA 517(0.72%)
  13. Oxford 500(0.70%)
  14. Ottawa 466(0.65%)
  15. San Francisco 459(0.64%)
  16. Arlington 457(0.64%)
  17. Chicago 429(0.60%)
  18. Durham 393(0.55%)
  19. Boston 367(0.51%)
  20. Montreal 364(0.51%)

I’ve known who I was reaching for a while – I get informal notes and phone calls from people at various institutions letting me know they liked (mostly) or disliked/had issues with (sometimes) things I have written. Compared to many blogs, I don’t get that many readers. But my readers are my target audience – they are the folks who work in development and climate change. Well, that, and my students here at the University of South Carolina (hence the Columbia and Irmo numbers).

The one big problem for me, and this blog, has been the level of effort it requires, and the ways in which it could (and could not) be used in my primary sectors of employment, academia and development consulting. Though the world is changing fast, the fact is most people still will not take a blog post as seriously as an academic article. That is probably a good thing – there is a lot of crap out on blogs. At the same time, there are really good blogs out there, some of which produce better work/scholarship than you find in the peer-reviewed literature. Finding ways to help people sort out what is good and what is crap, and finding ways to make social media/blog posts viable sources for academic and consulting work, is important to me.

So, starting today, I have linked this blog to The Winnower. When I produce a post with enough intellectual content, I will cross-post it to the Winnower, where it will be subject to a review process, after which it will receive a DOI, making it a real publication in the eyes of many journals and other sources (hell, it will fit under “other academic contributions” on my CV, so there). I’m excited about what The Winnower is trying to do (as you might already know I find academic publishing structures deeply frustrating: just look here, here, here, and here), and if my work serves to further their mission, and their efforts serve to further blur the lines between the ways in which I disseminate my work, I’m happy to give it a go.

Here is my author page at The Winnower. I’ve currently got six old posts up for review – six posts that were viewed by an average of well over a thousand readers each. So I know you all care about these posts and topics. Go ahead and review them, comment on them, help me make them better…and help The Winnower succeed.

Welcome to the future. Maybe.

Five and half years ago, at the end of the spring semester of 2009, I sat down and over the course of 30 days drafted my book Delivering Development. The book was, for me, many things: an effort to impose a sort of narrative on the work I’d been doing for 12 years in Ghana and other parts of Africa; an effort to escape the increasingly claustrophobic confines of academic writing and debates; and an effort to exorcise the growing frustration and isolation I felt as an academic working on international development in a changing climate, but without a meaningful network into any development donors. Most importantly, however, it was a 90,000 word scream at the field that could be summarized in three sentences:

  1. Most of the time, we have no idea what the global poor are doing or why they are doing it.
  2. Because of this, most of our projects are designed for what we think is going on, which rarely aligns with reality
  3. This is why so many development projects fail, and if we keep doing this, the consequences will get dire

The book had a generous reception, received very fair (if sometimes a bit harsh) reviews, and actually sold a decent number of copies (at least by the standards of the modern publishing industry, which was in full collapse by the time the book appeared in January 2011). Maybe most gratifying, I heard from a lot of people who read the book and who heard the message, or for whom the book articulated concerns they had felt in their jobs.

This is not to say the book is without flaws. For example, the second half of the book, the part addressing the implications of being wrong about the global poor, was weaker than the first – and this is very clear to me now, as the former employee of a development donor. Were I writing the book now, I would do practically nothing to the first half, but I would revise several parts of the second half (and the very dated scenarios chapter really needs revision at this point, anyway). But, five and a half years after I drafted it, I can still say one thing clearly.


Well, I was right about point #1 above, anyway. The newest World Development Report from the World Bank has empirically demonstrated what was so clear to me and many others, and what I think I did a very nice job of illustrating in Delivering Development: most people engaged in the modern development industry have very little understanding of the lives and thought processes of the global poor, the very people that industry is meant to serve. Chapter 10 is perfectly titled: “The biases of development professionals.” All credit to the authors of the report for finally turning the analytic lens on development itself, as it would have been all too easy to simply talk about the global poor through the lens of perception and bias. And when the report turns to development professionals’ perceptions…for the love of God. Just look at the findings on page 188. No, wait, let me show you some here:

Screen Shot 2014-12-21 at 10.05.06 PM


For those who are chart-challenged, let me walk you through this. In three settings, the survey asked development professionals what percentage of their beneficiaries thought “what happens in the future depends on me.” For the bottom third, the professionals assumed very few people would say this. Except that a huge number of very poor people said this, in all settings. In short, the development professionals were totally wrong about what these people thought, which means they don’t understand their mindsets, motivations, etc. Holy crap, folks. This isn’t a near miss. This is I-have-no-idea-what-I-am-talking-about stuff here. These are the error bars on the initial ideas that lead to projects and programs at development donors.

WDR’s frames these findings in pretty stark terms (page 180):

Perhaps the most pressing concern is whether development professionals understand the circumstances in which the beneficiaries of their policies actually live and the beliefs and attitudes that shape their lives.

And their proposed solution is equally pointed (page 190):

For project and program design, development professionals should “eat their own dog food”: that is, they should try to experience firsthand the programs and projects they design.

Yes. Or failing that, they should really start either reading the work of people who can provide that experience for them, or start funding the people who can generate the data that allows for this experience (metaphorically).

On one hand, I am thrilled to see this point in mainstream development conversation. On the other…I said this five years ago, and not that many people cared. Now the World Bank says it…or maybe more to the point, the World Bank says it in terms of behavioral economics, and everyone gets excited. Well, my feelings on this are pretty clear:

  1. Just putting this in terms of behavioral economics is actually putting the argument out there in the least threatening manner possible, as it is still an argument from economics that preserves that disciplinary perspective’s position of superiority in development
  2. The things that behavioral economics have been “discovering” about the global poor that anthropology, geography, sociology, and social history have been saying for decades. Further, their analyses generally lack explanatory rigor or anything resembling external validity – see my posts here, here, and here.

Also, the WDR never makes a case for why we should care that we are probably misunderstanding/ misrepresenting the global poor. As a result, this just reads as an extended “oopsie!” piece that needs not be seriously addressed as long as we look a little sheepish – then we can get back to work. But getting this stuff wrong is really, really important – this was the central point of the second half of Delivering Development (a point that Duncan Green unfortunately missed in his review). We can design projects that not only fail to make things better, we can actually make things much worse: we can kill people by accident. We can gum up the global environment, which is not going to only hurt some distant, abstract global poor person – it will hit those in the richest countries, too. We can screw up the global economy, another entity that knows few borders and over which nobody has complete control. This is not “oopsie!” This is a disaster that requires serious attention and redress.

So, good first step World Bank, but not far enough. Delivering Development still goes a lot further than you are willing to now. Delivering Development goes much further than behavioral development economics has gone, or really can go. Time to catch up to the real nature of this problem, and the real challenges it presents. Time to catch up to things I was writing five years ago, before it’s too late.

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