One of the pleasures of working on FINclusionLab has been getting my work translated into the languages of most of the countries we cover: French, Spanish, and Turkish. By happy coincidence these are also most of the languages that I either speak or am making a serious effort to learn. I am not fluent enough in any of them to do the translating myself, but I can at least understand the translations that I’m applying, and read domestic press coverage when it comes out. It’s not always easy to get key stakeholders to actually use the tools we’re making for them, so it was particularly nice to see Mexico’s national bank trumpeting the release of the financial inclusion dashboards we made:
La CNBV presentó los mapas interactivos para el análisis de la inclusión financiera en México
[Google’s translation is not bad, albeit even wordier than an already government-speak heavy press release]
I was recently party to a discussion about a code of conduct for an internet community, in which we found ourselves trying to delineate the difference between welcome and unwelcome forms of nationalism. The moderator found a better way to work around that, but the question got me thinking. I am generally anti-nationalist, but there are forms of nationalism that I do tend to sympathise with, and it’s worth trying to clarify why. To start making sense of implicit demarcations like this, I find it helpful to start with a list of opposites in my own feelings: Continue reading “What if the Nation State is the problem?”
9 years ago, I was part of a small team that founded what is now Happiness Alliance. Our goal was to get happiness taken seriously as the primary objective of public policy, instead of the status quo in which governments maximise economic indicators without questioning whether they are even good metrics of the economy, never mind why we prioritise the economy above everything else in life. This is not a new idea; in fact I still think Bobby Kennedy said it best in 1968:
…Our Gross National Product, now, is over $800 billion dollars a year, but that Gross National Product – if we judge the United States of America by that – that Gross National Product counts air pollution and cigarette advertising, and ambulances to clear our highways of carnage. It counts special locks for our doors and the jails for the people who break them. It counts the destruction of the redwood and the loss of our natural wonder in chaotic sprawl. It counts napalm and counts nuclear warheads and armored cars for the police to fight the riots in our cities. It counts Whitman’s rifle and Speck’s knife, and the television programs which glorify violence in order to sell toys to our children. Yet the gross national product does not allow for the health of our children, the quality of their education or the joy of their play. It does not include the beauty of our poetry or the strength of our marriages, the intelligence of our public debate or the integrity of our public officials. It measures neither our wit nor our courage, neither our wisdom nor our learning, neither our compassion nor our devotion to our country, it measures everything in short, except that which makes life worthwhile….
And yet, four decades later we still encountered endless skepticism about the whole idea. Those who accepted the premise kept telling us that it was futile because public policy interventions never make a measurable difference to happiness anyway.
Sadly, recent work by the Happiness Alliance (I am no longer involved, but cheer them on from the sidelines) has proven the skeptics wrong in the most negative way possible. We can now clearly see that the grinding awfulness of 2017 was not just in my head or my social circle, but has added up to a measurable decrease in self-reported happiness:
There are a couple of important caveats to understand here:
- This is a “convenience sample”, meaning it has not been weighted to be fully representative of the population –but there’s no reason to expect that 2017’s sample will have new or different biases, having been recruited in the same ways as previous years’.
- We don’t know where every survey taker was, so it’s impossible to compare US-based respondents with those elsewhere –but we do know that the vast majority of respondents are in the US.
It’s not a huge effect size—only 5-6%—but it is highly statistically significant, and when I remember all the people saying we’d never see any changes at all I can’t help but be impressed. And glad that this thing I helped start has had the staying power to be able to look at trends over years.
It seems that totally unhelpful news graphics are not exactly a new problem. Here is Mark Twain’s take on them, during the Franco-Prussian War of 1870:
TO THE READER.
The accompanying map explains itself.
The idea of this map is not original with me, but is borrowed from the “Tribune” and the other great metropolitan journals.
I claim no other merit for this production (if I may so call it) than that it is accurate. The main blemish of the city-paper maps of which it is an imitation, is, that in them more attention seems paid to artistic picturesqueness than geographical reliability. …[read more]
Original image courtesy of Mapping As A Process, which published a deep dive on all the different variants which have been published, their history and reception.
My biggest project for the past few years has been an ongoing series of workbooks about access to financial services in Africa, Asia & Latin America. I do this work as a subcontractor to an NGO called MIX, whose CEO recently gave an interview concisely explaining why we do this work and what it’s useful for. This paragraph gets to the heart of it:
FINclusion Lab creates single datasets and databases where previously siloes existed. For example, the data – which primarily includes access point location and demand-side data like population density, cellular coverage, poverty rates and the like – is usually found in project documents (PDFs), or separate online locations managed by regulators, or even individual Excel files from financial institutions. Bringing it all together in one place allows users – often regulators, financial institutions or others – to conduct analyses across different types of data including service points (geo-coded data), credit/deposit usage and demographics. It also allows users to visualize the data across geographies and drill down to more specific locales. Because we publish this data in a highly interactive format, users can explore the data based on their specific questions or interests. For example, a user can explore a particular district or type of financial service provider, or pick a reference period to view trends.
I’ve also been working behind the scenes on the infrastructure we use to conduct and share analyses, simplifying the toolchain and making updates & translations easier to apply. This included rebuilding a venerable Tableau template from the ground up, and here’s the first country workbook we’ve published in the new template:
Today I watched the People’s Tribunal outside the Northwest Detention Center. The testimonies were all stories about individuals currently detained there, told by people who had interviewed them this weekend, because the detainees aren’t allowed to speak for themselves. We heard painful accounts of the petty reasons people end up detained there, the barriers to their getting a fair hearing once caught up in the punitive immigration system, poor conditions in detention, and above all how the system dehumanises detainees and guards alike. I was reminded alternately of Josef K and Ivan Denisovich, two archetypes this country likes to pretend it’s above creating.
But that’s not what I want to tell you about. Hopefully you already know about the evils of the US immigration system, and the abuses at detention centers, and if you don’t then NWDC Resistance has a better backgrounder than I could write. I want to look at a question of geography: the location of the center itself, and all the ways it reminds us that the immigration system does not value our fellow prisoners.
Continue reading “One island of the archipelago”
When I restarted this blog, I decided to focus on geography, and generally steer clear of either really personal posts or the political issues of the day. But sometimes that distinction doesn’t really hold up. The US’s treatment of people who were brought here as children is an example: it’s just the sort of current-politics issue I didn’t want to be talking about here, but it’s also somewhat on topic and so intensely personal for me that I can’t leave it alone.
I’ll start with some biographical information for context. I was born in Turkey, but when I was very young the country went through a period of political violence that my parents very reasonably decided that we should get away from. Because my great-grandfather had shrewdly taken advantage of the brief period when İstanbul was colonised, we had EU citizenship, so we were able to move to Britain as legal, documented, above-board immigrants. Thus my lifetime of being the most privileged sort of immigrant began before I could even speak in sentences. Continue reading “DACA”
Palestinians in the Palestinian-administered parts of the West Bank live in a completely separate reality from Israelis just a few miles away, to the point that many roads are only open to one of those populations. This turns out to be a real challenge for crowdsourced navigation apps like Waze and Google Maps. Although the linked article makes much of the countries each service is based in, I find this more interesting as a study in the accidental politicisation of maps. I don’t think Waze is trying to handicap Palestinians; it’s stuck in a model of trying to show one consensus reality, when what’s a great route for one driver may be illegal or unacceptably dangerous for another.
I just read about some very cool big data archaeology. A group of economists and historians constructed a dataset from 4,000-year-old cuneiform tablets, adding up to hundreds of records of trade transactions between cities. They treated trade volumes as proxies for the distance between cities, presumably calibrated using trade between pairs of cities with known locations. But many of these cities are lost to modern people, and that’s where this gets really interesting: if archaeological site A traded with lost city B, the researchers could plot a radius around A for the likely distance to B. With enough known locations, they can start to narrow down where the lost cities must be:
Source: Washington Post. Original paper: Trade, merchants, and the lost cities of the Bronze Age.
Last week I ranted about a poorly executed report claiming to show which properties around the US are at risk of climate change driven flooding. Peter Abrahamsen responded with:
Also, mean sea level, however it’s measured, doesn’t tell you who’s at risk of flooding.
and then pointed me at a couple of much better examples, most notably the Victoria, BC Capital Regional District’s climate change modeling project. I think it’s worth looking at all the other questions that would have to be answered to really get this right. Before diving in, I want to make clear that I’m not piling on Zillow any more: last week’s post was about flaws they should have figured out as a real estate data company, while most of what’s below will be details that they never claimed expertise in or took a position on. Continue reading “What would it take to predict climate change inundation well?”