In 1937, Joseph Stalin ordered a radical census of the Soviet Union. The data reflect certain uncomfortable facts – in particular, the damping of population growth in areas devastated by the famine of 1933 – and the government of Stalin therefore abolished the release of the results of the survey. Several statistical workers of the high -level government responsible for the census were then imprisoned and apparently executed. Although the Soviet authorities proudly deceive national statistics that glorified the achievements of the USSR, all the figures that did not correspond to the preferred story were buried.
A few weeks ago, following the publication of “disappointing” data from the office of Labor Statistics (BLS), Donald Trump dismissed the Labor Statistics Commissioner, Dr. Erika Mcentarfer, and said that the figures were “rigged”. He also announced his intention to order an unprecedented census of the American population (they occur every 10 years and the next one should be in 2030) by emphasizing that this census “will not count illegal immigrants”. The actual objective is probably to deliver a set of population estimates that could be used to reappear seats and districts of the congress before the mid -term elections of 2026 and ensure favorable conditions for the republican control of the Congress – although it is not clear that there is enough time or conference support to get there. The administration would also have “updated” the national climate assessments and various important sources of data on subjects related to climate and public health have disappeared. In addition to all this, Trump’s Ministry of Justice has launched an investigation into statistics on the crime of the Metropolitan Police of DC, alleging that the largely reported drop in violent crimes of DC 2024 – the lowest total number of violent crimes recorded in the city in 30 years – are a distortion, fueled by falsified or manipulated statistics. One could say that the burden of “false data” is only a close cousin of “false news” and that all this is normal for the course of an administration which insists on an alternative reality is the truth. But this model can also generate a specifically disturbing (and typically Soviet) state of things: the public conviction that all “political” data is false, that one cannot generally trust the statistics. We must resist this paradigm shift, as it mainly serves an anchored authoritarianism.
It was ultimately a common feeling in the Soviet Union that one could never trust the “official figures” because they were widely manipulated to serve political interests. (At least, it is the feeling reported by my parents, who grew up in the Soviet Baltic States in the 1960s and 1970s – I was an infant when we left at the end of the 80s, so I cannot report a lot of hands. Family, it is difficult to widen your point of view to include the experiences of people in very different circumstances of yours. This type of parish world with little points of reference is bad and The solidarity of the construction between the groups. Things get useless – just do what you can get out of it.
A political culture without confidence in data or statistics is also that which will be based more on opaque decisions taken by the closed -closed elites. In his influential historical study of the rise of quantitative bureaucracy, the historian Thomas Porter emphasizes that the basis of political decisions on calculated costs and digital advantages reduces the role of “local” discretion and can have a homogenizing effect, which can strengthen control of the centralized state. The back of the medal of this piece is that it also deposits people in power of a part of their authority by allowing a certain degree of transparency and public rupture: if a huge government project must be justified by reference to certain cost-dispatches, these calculations can be verified and disputed by various parts. If a government agency requires the documentation of progress on initiatives, proof that public funds are spent in an appropriate manner and proofs on profits and in how much less space for corruption and mismanagement provided that the independent parties have access to the relevant information. Without credible data that reflects facts on the ground, how can the public repel an invented story of “crisis”, concocted to justify the invocation of emergency powers?
Anyone spending time working with data is perfectly aware that there is a lot of choice in the collection or processing of data – there are many “decision points” on what to include, how to define or measure things, etc. Indeed, insofar as the data is used to tell stories about complex things such as the state of the economy or the health of a population, different choices of data collection or analysis can to a certain extent provide support to different stories, including predetermined stories if an unscrupulous analyst is on her. But it does not follow that “everything happens” or that the statistics are not meaningful. There are better ways to collect and analyze data, both reasonable and absurd means of answering empirical questions such as “DC crime rates increase or decrease?” More importantly, when government statistics are managed by qualified and non -supporter officials and relevant figures can be disputed, debated and disputed, we have a democratic basis to guide our institutions to better political decisions. Public importance data must be accessible to the public and not hidden.
Trump’s assault against data integrity is not the worst of its ongoing abuses – the public should be more immediately indignant by masked agents who disappear from people on the street and the National Guard occupying urban centers – but this model of actions vis -à -vis official statistics should be extremely alarming. It is a slow boil: if we reach the point where nobody trusts the numbers because everything is “false data”, it will be too late to resist and too difficult to undo the damage. The opposition must block the appointments of unskilled and clearly biased candidates to direct the BLS and other agencies responsible for data management. We must resist excessive interference in data collection, whether at the level of the American census or at the level of the city government. On the contrary, we should invest in initiatives that strengthen public confidence and understanding social, economic and environmental data that can be used to guide the decisions that affect the well-being of our communities.
