The rise and fall of sampling surveys in Norway 1875-1906

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The Rise and Fall of Sampling Surveys in Norway, 1875–1906

Einar Lie

Science in Context / Volume 15 / Issue 03 / September 2002, pp 385 - 409DOI: 10.1017/S0269889702000534, Published online: 14 January 2003

Link to this article: http://journals.cambridge.org/abstract_S0269889702000534

How to cite this article:Einar Lie (2002). The Rise and Fall of Sampling Surveys in Norway, 1875–1906. Science in Context, 15, pp 385-409doi:10.1017/S0269889702000534

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The Rise and Fall of Sampling Surveys in Norway, 1875–1906

Einar Lie

Center for Technology, Innovation and Culture, University of Oslo

Argument

Norwegian statisticians were pioneers in the development of sampling techniques for socialand economic investigations in the late nineteenth century. After a few years of extensive useof sampling surveys in large-scale social and economic investigations, the method fell out ofuse in the early 1900s. This article supports Alain Desrosières’ argument that the emergenceof sampling procedures in social investigations must be seen in relation to a modern“individualistic” view of society. But the importance of the institutional setting is also stressed:The way statistical research was connected to the power and resources of the State within theCentral Bureau of Statistics (CBS) was a central element in the development andimplementation of the new technique. A separate argument is presented to explain why themethod suddenly lost ground in Norway and the general director of the CBS stoppedpromoting his method in the meetings of the International Statistical Institute. Theexplanation is probably to be found in a large and politically important survey in the 1890sthat was attacked by a group of actuaries from private insurance firms. The heated and long-lasting debate turned into a question about trust in the new method and the reputation of thehead of CBS as a statistical expert. The necessary trust and confidence was lost when the CBSin 1906 had to admit that important estimates from this survey obviously were erroneous.

In connection with its one-hundredth anniversary in 1976, the Central Bureau ofStatistics of Norway published a slim hardcover volume as part of its research reportseries. This book, entitled The Representative Method of Statistical Surveys, was originallywritten in 1897 by the Bureau’s first Director General, Anders Nicolai Kiaer(1838–1919). By 1976, the Central Bureau of Statistics had been using representativesampling extensively for around 25 years, after having imported the practice fromAmerican social scientists in the early postwar years. When they examined theinternational publications on the history of statistics, the employees at the Bureaudiscovered that the proclaimed originator was actually one of their own.

A method of sampling had been used in Norway in some investigations fromthe mid-1870s to about 1900. It perhaps reached its pinnacle in the 1890s when themethod was used extensively in a large-scale study carried out in connection with aproposed social insurance act and was also used to estimate the Norwegian nationalincome for the first time. However, just after the turn of the century, its popularity

Science in Context 15(3), 385–409 (2002). Copyright © Cambridge University PressDOI: 10.1017/S0269889702000534 Printed in the United Kingdom

eroded. When it reemerged as a vital part of statistical methodology after World WarII, its origin seemed to have been forgotten in Norway.

From the 1930s the theories and methods of sampling have been stronglyintegrated in the corpus of statistical theory. Today, sampling techniques areindispensable tools for statistical offices and social scientists all over the world, andthey have a profound influence on the development of knowledge for science andpolitics. But the prehistory of sampling surveys, not only in Norway, seems abrupt –both in the method’s origin and its demise. When Kiaer presented his samplingmethod for the first time at the meeting of the International Statistical Institute (ISI)in Bern in 1895, his work did not seem to rest on the shoulders of other scholars, andit is hard to spot the continuity from earlier work on statistical theory and method.His theory was discussed at several ISI meetings between 1895 and 1903, where it wascriticized from several different angles. Then it dropped out of the agenda of ISI untilit re-emerged at the meeting in Rome in 1925.

This article will focus mainly on the rise and fall of the sampling method inNorway. Its reception in international arenas has already been described and analyzedin detail in several works and will be treated here only briefly. It is also clear thatthe Norwegian case is a special one. The first spokesman of the new method in theinternational statistical society was the Norwegian statistician A. N. Kiaer. There isalso the puzzle of its peculiar disappearance. Kruskal and Mosteller pondered thequestion of why Kiaer did not champion his method in ISI after 1903: “[It could not]have been Kiaer’s inactivity or incapacity – he published through 1919, the year of hisdeath. What was it about la Belle Époque that created a representative hiatus? We donot know” (Kruskal and Mosteller 1980).

When we also take into account that the method fell out of use in largerNorwegian surveys at about the same time, the question seems no less intriguing. DidKiaer lose faith in his method? Was he discouraged by the criticism he encounteredat the ISI meetings? Or are the answers to be found in Norway itself and the way hismethod was used to investigate highly controversial matters? I will start at thebeginning of the story and deal with these questions later.

Representative Samples, Individualism, and National Surveys

How should geneses of the method be explained? Some of the epistemological andpolitical prerequisites for employing the statistical concept of representativeness havebeen discussed at length by Alain Desrosières (1990, 1991, 1998) in his studies of theprehistory of representative sampling. His analysis provides an excellent starting pointfor this discussion. Desrosières points to two major transformations that took placefrom about 1850 to the 1920s and 1930s. The first is a change in the norms dictatinghow scholars were to go about describing the social world – or more specifically, howto generalize social inquiries, how to move from the studies of a part to conclusionsabout a whole. Desrosières makes a strong argument for seeing representative

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sampling as a social technology deeply embedded in a “modern” or “individualistic”view of society. In this view, individuals are given primacy in the constituency ofsociety. Individuals are seen as “atomized” in the sense that they are not totallysubsumed under any particular grouping (“nation,” “society,” sometimes “class”).They can be – and mainly are – studied in terms of various characteristics that can beascribed to them for various political or analytical purposes: consumption patterns,level of education, political sympathies, and so on. These are characteristics that canbe measured without regard to a person’s place in a social network or the order ofsociety.

This view replaces a society described in holistic terms, where the social wholeexists prior to and above the individual. The social generalizations associated with thisview of society are those where “typical” individuals or families are seen to representtheir group or class. In the case of, for example, the household studies carried out byLe Play, these were often persons chosen from existing local networks, as Desrosièresdemonstrates. They were normally not typical in the sense of bearing average valuesof some supradefined features (income, opinions), but they made good subjects forstudy and as such represented the norms and functioning of their communities. Thismade sense as long as the surveys did not aim at describing variances or aggregates ofindividual characteristics. These kinds of generalizations were not universal, however,and this argument accounts well for statistical practices in France but poorly forBritain and especially Germany, which I will come back to later.

The second major transformation has to do with the geographical orientation ofthe surveys. European social surveys up to the end of the nineteenth century were,with very few exceptions, locally orientated. Social problems were seen as beingrelated to specific rural or urban areas impoverished by industrialization processes orchanges in the natural environment, and the problems were predominantly handledby local authorities. This way of identifying problems did not call for cross-regionalstudies or comparisons between classes or social layers. The quest for informationabout social and economic phenomena on a national basis is a companion of thewelfare state and national markets. In Desrosières’s analysis, the statistical problemof representativeness first appears when social problems are moved from the local tothe national scene. This creates a new “whole” that must be constructed either froma census describing a certain characteristic of the complete population or from a“sample” of individuals drawn from quite different social networks.

In the latter case, “sampling” presupposes that actors are sorted, classified, andencoded according to specific properties or characteristics, and that it makes sense tocompare or sum up these characteristics derived from individuals from differentgroups and regions. “The basic cognitive move that was made was to isolateindividuals from each other, [and] ignore whatever relations they might have,” asPeter Wagner (1994, 106) writes. Returning to Norwegian statistics and society, it isnot only of interest whether the surveys were aimed at local or national questions.The new – and it is tempting to say true – society of statistics is one where the

Sampling Surveys in Norway, 1875–1906 387

statistician constructs groups or social strata independent of current perceptions ofwho and what people are, with the purpose of comparing groups or adding themtogether to form a national whole. When this is the predominant way of analyzingsociety, it is not expected that the legitimacy of sampling techniques would be calledinto question.

Background: Statistics in Norway before 1870

In the first half of the nineteenth century, Norwegian statistics were dominated bywritings in the German tradition, with its comprehensive, verbal description of thestates. Eilert Sundt’s (1817–1875) social and demographic investigations came tobreak radically with this tradition.1 Sundt, often described in contemporary Norwayas “our first and greatest social scientist,” conducted’s surveys in the 1850s and 60squantitative surveys that included the whole nation, both geographically andsocially.

The studies from the peak of Sundt’s period as a social investigator werecharacterized by a combination of interviews and in-depth studies of traditions andcustoms in local communities and of analyses of extensive quantitative material. Themost recent are clearly inspired by Adolphe Quetelet. We know that Sundt readQuetelet. Seip has demonstrated how Sundt followed the Belgian statistician virtuallyverbatim in some of his descriptions of social regularities (Seip 1983). But there isgood reason to take a special look at where Sundt deviated from Quetelet. Quetelet’sconstruction of l’homme type implies a tendency towards determinism and reluctanceto consider variation. In Quetelet’s conceptualization of statistics, observations thatdeviate from the norm result either from measurement errors or “errors” in theindividual. The underlying characteristics of all human beings, both physical andmoral, were assumed to be the same. This kind of conceptualization does not inspirestudies that attempt to map characteristics of different groups through sample surveysor in other ways: The study of different groups presupposes that there are in factdifferences between groups. Quetelet thus never carried out surveys of his own, butrather concentrated on finding regularities in administrative statistics that had alreadybeen compiled (Lazarfeld 1961). Sundt, on the other hand, was less deterministic andhad great faith in the effects of social reform. His causal relationships and constantswere also geographically distinct and temporally specific (Lie 2001).

In 1857, Sundt conducted a national study on temperance, and in methodologicalterms this was probably one of the most advanced studies he undertook. The aim ofthe study was to make systematic comparisons of alcohol consumption amongdifferent classes and regions. A year later he carried out his first study on poverty inthe nation’s capital, Christiania. This was the first time he turned his quantitative andqualitative skills to a modern urban society. In this study, Sundt explicitly reflects

1 The only broader study of Sundt’s work in English is Allwood 1957.

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upon the differences between traditional society and modern society, the contours ofwhich he saw developing in the rapidly expanding Christiania. These reflectionsindicate a more individualistic and quantitative direction: In the villages, “custom”provided clear perceptions of oneself and one’s role in life, and there were fixedexpectations about social behavior. “Custom determines how one should walk downthe road, greet others, respond to others, and interact with others in a work or socialcontext; in short, it dictates how young people, through all phases of life, shouldbehave, and they are always being watched by parents and acquaintances, who standready to punish the slightest infraction of these traditions” (Sundt 1857, 76). The localsociety and its norms and rules kept young people in their place, for better or forworse. In the city, there was no fixed, all-encompassing set of conventions; it wassimultaneously a “den of iniquity and the birthplace of civilization” (ibid., 79). Thepossibilities for both social degradation and advancement were great.

Here Sundt provides an indirect explanation of why his analysis of urban society issomewhat less directed towards revealing and analyzing norm structures, which wasmore typical in other studies of rural societies. The traditional society can and shouldbe studied as a collective. It is unnatural to study the individual outside his collectivity,to not mention the social conventions that shape his society. The city, however, is lesswell suited to this kind of collective approach: The norms of the city are bothambiguous and less influential. The individual’s place in urban society cannot bederived directly from the whole, as it can for the son of a struggling cotter (husmann)in Romerike. In Christiania, it was necessary to look at the individual’s occupation,where he lived, how many pieces of furniture he had in his living room, and whetherhe had books or newspapers in his residence (as was quantified in the study of workersin Christiania). In short, this development is one of the main ingredients in the socialchange that paved the way for a social science that was both quantitative andindividualistic at the same time.

Even as early as in Sundt’s work it is apparent that a local perspective andorientation had become outdated, and Sundt classified and coded his subjects on thebasis of certain characteristics rather than their rank in the established socialcategories. With respect to the transition from a local to a national perspective, it isimportant to realize that a national study meant very different things in Norway andthe major European countries. In the mid-1850s, Norway’s entire population wasonly about one-and-a-half times greater than the population of London’s East End,while it was distributed over an area much greater than all of the British Isles puttogether. At the same time, it is noteworthy that the Norwegian statistical traditionbefore Sundt was national, in keeping with German role models. In the late 1700s,during Norway’s union with Denmark, there was a significant amount of literatureon local and regional statistical topography. After 1814, when Norway became anindependent nation-state with an advanced democratic constitution (seen in aEuropean context), the most important works that can be considered statistical havethe nation as a theme.


Sundt’s social research thus evolved quickly into differentiated, national studies. Inorder to explain this early development, it is unquestionably important to considerthat Norway’s population was ethnically homogenous; there were differences incustom, but in the views of the time period, it was the same people being studied.2

The lack of an economic upper class of any significance meant that Norway could becharacterized as a relatively egalitarian society. At several international congresses,Kiaer classified this as an advantage for the use of sampling surveys, but withoutclarifying what he meant. What must be important in this respect is not the equalityas it can be measured by technical means, for instance an income distribution. It is theperception that all the individuals can be compared. Norway was politically dividedinto groups comprising civil servants (embetsmenn), the bourgeoisie (borgere), andfarmers, but only the first group can be characterized as a national elite that is difficultto compare with others. However, the standing of the civil servants was weakenedfrom the 1860s. At that time there was a shift in historical research and it becamemore and more common for historians to claim that the common people werebearers of “Norwegian-ness,” rather than the sense of nationality being borne by theelites (Fulsås 1999). In general, thinking in collective terms – where individuals wereseen as societal members on the basis of their membership in certain classes or groupswith special duties, rights and functions – was challenged early on in Norway(regarding Schweigaard’s views, see Sørensen 1988, 28–34; regarding Aschehoug’s,see Seip 1975, 152–155). Seen in this light, the ground was probably more fertile inNorway for the type of survey that Sundt conducted than it was in the more class-divided societies in Europe.

The “Public Bureaucrats” and the First Sampling Surveys

In 1866, the 28-year-old Anders Nicolai Kiaer was appointed head of the State’sstatistical office. Two years later, Kiaer hired an old college friend and travelingcompanion when he studied in Paris, Jakob Neumann Mohn, as his second-in-command at the office. Mohn had worked closely for several years with EilertSundt, who was a source of inspiration also for Kiaer. During the course of the next15 years, Kiaer and Mohn would revolutionize Norwegian statistics. After only a fewyears, in 1876, the Ministry of the Interior’s office for processing figures wasreorganized to become a partially independent directorate, the Central Bureau ofStatistics, with a considerable amount of research activity.

2 In Sundt’s perhaps most advanced statistical study of temperance in Norway, he does not look at thenorthernmost counties because he perceives the differences between Norwegians on the one hand, and Samiand people of Finnish stock (kvaener) on the other, as so great that the latter had to be studied separately fromthe rest of the population (Sundt 1857).

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Kiaer and Mohn, thus became “public bureaucrats,” carrying out their research andreport-writing from the governmental office of statistics. Perhaps in some respectstheir position posed a threat to their creativity and the development of radical newways of thinking. Not only was the pressure from their daily workload undoubtedlygreat, the process of being integrated into the political and administrative systems thatencompassed the official statistics must have created tremendous pressure to conform.With the exception of contributions from Kiaer and his Prussian colleague ErnstEngel, revolutionary thinking in social statistics and methodological development didnot originate in the public bureaucracies but rather came from academics andenthusiastic and often well educated amateurs. On the other hand, their placement inthe bureaucracy afforded them a great opportunity to link social and economic issuesthrough the development of official statistics. Sundt’s surveys show that he, too,depended on cooperation from local civil servants. While the statisticians did not havegreater opportunities to ask questions themselves from an office or bureau in theMinistry of the Interior, they could require local civil servants and other state agenciesto contribute to the studies. And this was crucial for the implementation of theirrepresentative surveys.

In his many statements and writings on the method of representative surveys, Kiaeralways let the story begin with his own study on the status of income and assets inNorway. (This has also become the official story of the emergence of the samplingsurveys in Norway; contemporary literature convey it as a result of a suddeninspiration by Kiaer in 1890.) But the history of sampling surveys has a pre-history.The first survey was carried out in connection with the expansion of agriculturalstatistics in the mid-1870s. It was planned by Mohn and conducted jointly by Mohnand his colleague Boye Strøm. The most essential figures regarding agriculturalproduction had until this point been gathered every ten years when farmers providedthe general census with figures on the number of animals they kept, as well as thevarious types of potatoes and grain they had sown. In connection with five-yearreports, the lensmenn (local sheriffs) provided discretionary estimates of how muchmilk each cow produced on the average, the yield of the potatoes and grain, and howmuch grain and potatoes had been sown and planted per acre soil.

For the 1871–1875 period, the statistical office agreed to take over and sort out theestimates made by the lensmenn. The lensmenn were told that instead of making aneducated guess about the average conditions in their township, they should collectinformation about just five farms in their township. These farms were supposed to“represent the normal conditions of the township”; they should be “statisticallynormal farms.” The instructions did not provide much more detail than this. On thebasis of the incoming material, the statisticians calculated the average grain and milkyield for each township. Along with the amount of seeds sown, in absolute terms andper acre, and the number of cattle – the latter was included as part of the populationcensus – the total production figures and area of cultivated land could be calculated.The average numbers for the entire country were then calculated as a weighted


average of the townships, where the number of cattle and sown seeds were alternatelyused as a basis for the weighting.3

It is not known how the many lensmenn proceeded. In the records of the statisticaloffice, we nevertheless find an invoice from a lensmann who wanted compensation forsome of the expenses he incurred in connection with the search for and survey ofnormal farms. It is clear here that the “representativeness” is given a traditionalinterpretation; it was persons with prominent positions in the local communities andnetworks that were selected. The lensmann’s report was even accompanied by atranscription from a meeting in the township council, where representatives wereselected. The mayor himself was one of the five – and the first chosen. The socialranking of the others is not known, but it appears in the discussions that all themembers of the township council knew the five by name and believed them to begood representatives of the township. Thus, in the only case we have informationabout, this was the procedure for determining “representativeness.”

The publication of the agricultural study was delayed for a number of years. Thusit also included the results of a comprehensive study of the cotters’ economicsituation, which was published in full in Norsk Retstidende. The study was carried outby Mohn, and apparently on his own initiative, that is, it does not appear to have beencommissioned by the government or the parliament. The objective of the study wasto look at the extent of the cotter class in the country, and to find variations in thenumber of livestock kept and the area of available cultivated land. In modernterminology, this was Mohn’s way of measuring the assets and income of the cotters.These factors were to be compared on a geographical basis as well as against the newlycalculated figures for the whole country. In this way Mohn had an implicitopportunity to compare the cotters to the farming class because, with a small margin,the national figures were very close to the sum of the cotters’ and the farmers’property and livelihood.

[The surveys] do not cover the entire country or all of its districts – this would have beena tremendous undertaking – but rather a selection of districts. One township has beenselected from each of the rural districts, namely the township where the number ofcotters approaches the average for the district in question. Information has been gatheredfrom 56 townships in the country, where the most recent census counted a populationof 188,850 people or about 1/8 of the entire rural population.. . . Because of therepresentative character ascribed to the selected districts, there can be little doubt that theresults in their essence could provide an expression of the true conditions, not only forthe entire country, but also for greater regions such as a diocese. (Mohn 1880, 4)

3 “Statistik angaaende den norsk jordbrug, fornemmelig i femaardsperioden 1871–75 og aaret 1875” (Statisticson Norwegian agriculture, especially in the five-year period 1871–75 and the year 1875). C. No 15. TheCentral Bureau of Statistics (Christiania 1875); instruction form, Statistics Norway’s Archive.

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All of the population registers were reviewed for all of these 56 townships. Theinformation that Mohn was after was reconstructed from the very detailedinformation about the socioeconomic status that was provided in the census.

A third sampling survey was conducted in 1888 when Boye Strøm calculated thegeographical and social consumption patterns of certain goods. This survey isinteresting because it had a specific and direct application and it anticipated themotivation and design of modern surveys. The point of departure for this study wasone of the recurrent discussions about how various toll and tax rates distributedburdens among various population groups. But there were no surveys that providedquantitative answers to this question. In the wake of a political discussion about thisissue, however, the Central Bureau of Statistics agreed to conduct a survey of this typefor the Ministry of Finance in the course of a few months; the result had to be readyquickly because it was to be used in the coming budget proposal in the Norwegianparliament, the Storting.

The consumer goods in question were sugar, coffee, and petroleum. The CentralBureau of Statistics had 18,000 questionnaires printed up with questions about eachfamily’s address, size (specified in terms of adults, children, servants, and “others”),and the head-of-household’s occupation – along with a series of questions about thefamily’s annual consumption of the three consumer goods. The families were thenasked to write down how they had calculated their annual consumption, and toexplain whether they believed that their consumption was significantly above orbelow the normal level among families in the area. These forms were distributedthrough the lensmenn. The instructions given to the local police authorities were tohand them out to households that “could be assumed to be reliable and whoseconsumption could be presumed to be within the normal range for the social class towhich the head of the household and the housewife belonged.” Strøm furtherspecified that it was not necessary to take into account the family’s size or social status,that the replies would be sorted and handled on the basis of precisely these criteria atthe Central Bureau of Statistics (Strøm 1889, 74–75).

There is a much greater occurrence of random sampling in this study than in theother surveys that were carried out while the method was in use in Norway. In Kiaer’sstudy there were, as I will discuss further on, certain elements of random sampling inthe final stages. But the entire survey’s rationale was built on a very purposiveselection process. Why Strøm’s survey to a larger degree was based on randomness isnot easy to explain on the basis of the survey’s objective. This could have been causedby the time constraints, or by Strøm’s view on sampling methods. None of theavailable documents indicate any consideration of these conditions.

The replies were to be sent directly to the Central Bureau of Statistics from thehouseholds. Of the 18,000 questionnaires sent out, 8,000 were returned and of theseabout ten percent were discounted “because it was quite clear that the questions weremisunderstood.” But Strøm believed that the remaining responses “largely provideda quite good impression.” The average consumption for seven social groups


was calculated on the basis of the remaining lists, and total household consump-tion was calculated from population census material. The total consumption was thencompared with import figures from the trade statistics to see whether the data wasreliable. The comparison showed clear deviations especially for petroleum: house-holds were supposed to have consumed 15 million liters per year while only 14million liters had been imported. In addition it was also clear that firms also usedimported petroleum, but no one knew how much. The calculated consumptionfigures were clearly too high at the national level. But Strøm summed up hisexperience as follows: “Apart from the deviations mentioned here, there is no reasonto doubt that the results basically reflect the true conditions, and they are especiallyassumed to be fully usable [viable] to show the distribution of consumption patternsamong the various districts and within the various social classes” (Strøm 1889, 74).

How much emphasis should be put on these three proto-proto-surveys? Inhindsight, the three contributions must each be seen as interesting in their own right.All of the surveys, and the cotter survey in particular, show that the originators of themethod had an idea about statistical representativeness and applied this to a practicalstudy. But whether or not Mohn and Strøm saw the method as truly ground-breakingis not clear. The introduction to the agricultural statistics from 1875 indicates thatMohn thought he had come up with a good idea, but not that it was a significantdiscovery. But it was from here that the method was developed, and it is difficult tosee any other particular steps – apart from perhaps Jerzy Neyman’s famousgeneralization and formalization of sampling methodology in 1934 – that can be saidto be as essential as this.

In a work on the history of the representative survey method from 1951, You PohSeng writes that Kiaer “only had his intuition and courage” (Seng 1951, 222). Givena fuller picture of the prehistory, the statement should be amended to say that he hadMohn’s intuition and his own courage.

Kiaer and His Major Surveys

Where do we stand in relation to what was presented earlier as the method’s socialprerequisites? The method is used in national surveys, but it does not seem to haveappeared as a consequence of a change of focus from a local to a national level. Thevery first survey to employ a statistical concept of representativeness, the agriculturalstudy, was merely an augmentation of an existing national statistic and did not addressany radically new issue.

The issue of “individualism,” as presented earlier, probably loses relevance as themethod became incorporated. The thought that one or more statisticians ex postwould have collectivist misgivings and stop studying people outside their socialcontexts seems absurd.

In Kiaer’s case, despite opinions about the quality of his previous work, it isnevertheless clear that the method was not particularly well established. There can

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thus be good reason to question the role of individualism, especially since Kiaer’ssocial views and statistical practice were so removed from any kind of holisticthinking. One factor is his completely consistent use of natural scientific analogiesand metaphors when he wanted to explain why his “representative method” wasintuitively correct: If you have two barrels with the same contents, one large and onesmall, you can discover the contents of the large one simply by collecting enoughsamples from the small one. And when you want to study the geology of a certainarea, you cannot just dig and scrape at rocks and soil everywhere; rather you mustexplore selected sites in minute detail. This was his crowning example, but he alsobrought in references to studies of flora and fauna, and especially meteorologicalobservations (Kiaer 1897; Kiaer [1897] 1976; Kiaer 1898–99; ISI 1896; ISI 1903; ISI1905). It is this kind of transfer of natural scientific discourse to the social sciences thatthe Frankfurter school characterizes as “technocratic.” The differences betweenpeople and barrels of herring or grain, or rocks, soil, rain, and sunshine include thefact that the latter do not enter into social networks or create any “social whole.” Anyproblems with drawing conclusions about the collective on the basis of the individualare thus annulled in nature-to-society transformed discourse.

Kiaer’s view on the relationship of the individual to society was otherwiseexpressed directly in his lecture “Om menneskets økonomisk vaerd” (On theeconomic value of mankind), held at the Economists’ Association in 1892. Thelecture was inspired by Ernst Engel’s article “Der Werth der Menschen,” but Kiaerattempted to expand and aggregate Engel’s reasoning in several directions. By makinga number of assumptions and classifying people into social classes, he calculated whatit would cost to bring a newborn child into the working force. The lecture dwelledon the technical issues involved in such a calculation, for example, the interest ratethat should be used in the capitalization of the investment made in the child in theform of upbringing and education. Kiaer was also aware of the “weaknesses” of hisapproach: He treated people as homogenous entities, but also noted that in theproduction of people there are “secondary and tertiary products.” In his conclusions,Kiaer systematically tried to find the conditions that held when an individualgenerated a social surplus and the conditions under which an individual wouldgenerate a social deficit. This was, however, met with heavy criticism (even) in theEconomist’s Association. All the discussants favored a way of thinking whereconclusions about the individual were deduced on the bases of the society’s needs andaims. But Kiaer argued programmatically individualistically: for him, all the entitieson the level of “society” were nothing less than the sum of individual entities (Kiaer[1897] 1976).

From the man to his work: the principle that permeated Kiaer’s work – which isthe entire key to understanding the strengths and weaknesses of his method – was tocreate “a nearly correct miniature picture of the entire study field” (Kiaer [1897]1976). This miniature should comprise almost exactly the same relative number ofpersons from each identified occupational group, as well as from each geographical


region (urban and rural, further divided into types of rural districts, large, medium,and small towns). Kiaer did not classify his data on the basis of the subject matter ofthe study, as is done in modern “stratified” sample surveys. On the contrary, hecreated a sample that was supposed to reflect reality as closely as possible, where“reality” was conceptualized as the picture of Norway reflected through thepopulation censuses.

In an analysis of Ernst Engel (1821–1896), Ian Hacking claims that Engel could nothave developed studies based on a representative sample because he did not think interms of probability theory. “The idea of representative sampling requires a conceptof statistical law that Engel simply lacked” (Hacking 1987, 383). The example ofKiaer calls that conclusion into question: Kiaer’s miniature model provides analternative to the path of sampling methodology founded on probability theory. I alsoquestion Hacking’s accuracy when he explains Engel’s statistical orientation bypointing out that he belonged to a historic school that was organic and non-individualistic. Engel’s use of household accounts must, in contrast to Le Play’s and hissuccessors, absolutely be considered individualistic, with an emphasis on comparisonsbetween individuals and aggregating from the individual to larger wholes (Desrosières1991). Le Play’s informants were, in contrast, selected with respect to their positionin the local social structures – and these social positions were analyzed with the aimof studying norms and conventions, not at adding up statistical characteristics fromthe individual level to aggregate groups. And Kiaer’s calculation of a person’seconomic value used one of Engel’s studies as a starting point. Based on the factorsdiscussed in this paper, it is difficult to find elements in Engel’s social and statisticalthinking that can explain why he did not use sampling surveys based on Mohn’s andKiaer’s principles.

Kiaer used his miniature model for the first time in connection with an incomeand asset study early in the 1890s. This survey used the income lists from thepopulation census in 1891 as a starting point. The complete material was thenreduced to a sample of 11,500 by way of a three-step process. First, a number of citiesand townships throughout the country were selected. These were to provide a“correct representation” of the entire country. This raises the question of what exactlywas to be “represented in a correct manner.” Kiaer, however, did not seem to feel theneed to ask that question in order to find his answer. In the first sample, the criterionwas the distribution of occupations with respect to the head-of-household’s positionwithin the main businesses and industries. In this way, Kiaer’s subjects comprised acomposition of cities and typical agriculture, fishing, and forestry townships thatprovided a correctly blended picture of the country as a whole. The second step inthe reduction process was to sort out persons (i.e., men) whose last name began withA, B, C, L, M, and N in the townships and the small towns, and only L, M, and Nin the country’s nine largest cities. The last two procedures, as Kiaer pointed out, weresupposed to function “in the same way as a lottery, where one carefully tries to avoidall of the elements that could be considered favorable for men in certain positions orthat belong to a certain social class.”

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While the results of the income and asset study were being processed, Kiaer startedon a new and far more ambitious study. Kiaer was a member of the parliamentarylabor commission established by Stortinget in 1894 to prepare a social insurance act(Folkeforsikringen). This was a politically controversial issue, one that would generatethousands of pages of recommendations, counter-recommendations, and newrecommendations over the course of the next couple of decades. The statistical basefor the labor commission was prepared by a separate secretariat led by the ReverendEugene Hanssen. The design of the study, however, was put together by Kiaer, whoalso advised the secretariat’s members during the implementation and subsequentprocessing of the material. These surveys played a key role in the debate on themajority proposal that was submitted, a proposal that aimed at introducing universaldisability insurance.4 It was clear that this act would incur enormous expenses; noother country had even come close to such a scheme in practical politics. Kiaer’sstatistics were to provide answers about how great the expenses associated with suchan insurance act would be, and whether the country’s economy would be able to bearthese costs.

The technical set-up was basically as follows: The commission decided that itwould gather statements about occupation, education, family status, health, income,etc., for a total of 80,000 people, both men and women. There was no one in thecommission, its secretariat, or the Central Bureau of Statistics who had mastered thecalculus of probability and could say anything about how certain the estimates of thenumber of people unable to work (invalids) would be by choosing this sample inparticular. Nowhere was a justification for the sample size of 80,000 to be found. Butthe figure was undeniably high, and Kiaer and the commission must have felt that itwas sufficiently large to result in reliable figures. Thus about 60,000 questionnaireswere distributed in the rural districts and 20,000 in the cities.

In the rural districts, the same basic set-up was followed as that used in the incomeand asset study from 1891, except the distribution of lists in the individual fogderier(historical administrative units between a county and a township) and townships wasexecuted with even more caution. Within each county, the townships were sortedinto the following district categories: agricultural, cattle raising, forestry, fishing,maritime, and industry. Then one or two townships were selected from each fogderi.To get a completely accurate representation of the range of occupations for eachcounty, it was also often necessary to reduce the number of questionnaires for sometownships and increase them for others. When this distribution was made, the

4 The majority recommendation was called “Indstilling til Lov om Invaliditets- og Alderdomsforsikring for detnorske Folk” (Recommendation for a Law on Disability and Social Security Insurance for the NorwegianPeople) (Christiania 1899). More recent literature has also referred to the proposal as if it also covered socialsecurity insurance, as the title of the proposal suggests. However, the proposal did not go further than to statethat disability as a result of aging should entitle an individual to welfare payments. A general social securityscheme was explicitly rejected.


enumerator’s personal judgment came into play. The enumerator had to choose “aspecific route” and “while following that route make sure that that he visited housesof different types within the vicinity, and make sure that he did not over-represent thetype of house that could be considered typical of the middle class, but rather includethose families and individuals on the route that were also wealthier and poorer thanaverage” (Kiaer 1897, 9). These principles were followed also in the selectionprocesses for the cities. A random sampling in the final phase was ensured, but theelement of purposive sampling dominated.

Kiaer’s way of making sure the sample was correct was to compare the compositionof the samples the enumerators had with the figures from the population censuses.This underlined the role of the miniature model: For cities and rural districts, and forboth men and women, the sample and the population census figures were compared.This applied to both the total size of the sample and the size after breaking it downinto the various occupational groups. Kiaer and the commission concluded that thefigures came close and had to be very reliable, but again it was guesstimation andintuition that decided the matter.5

The comprehensive study produced in reality two different complexes of statisticalinformation. The first was a new calculation of income conditions, and this wentdeeper and is theoretically and methodologically more interesting than the studybased on tax returns from 1891. Here Kiaer also undertook a comprehensivemapping of the value of unpaid work in the home and on the farms. The underlyingintention of this part of the study was to come up with a basis of facts that could beused in the discussion of how to finance the new insurance system. Nevertheless, Iwill here concentrate on the most controversial aspect of the study in the followingdiscussion about the majority recommendation: the estimated number of disabledpeople at the time, as well as the projected development in the number of disabled forthe years to come. This is what the insurance act was targeted at, and it was this figurethat would indicate the cost of the proposed act.

Kiaer landed in the middle of two controversies with his studies. When theparliamentary labor commission submitted its recommendation in late December1899, he had, as mentioned previously, already presented the principles behind thestudies at several meetings in ISI. Here he had received some support and muchcriticism. His reception in Norway, however, was to be far worse.

5 In the text, Kiaer pointed out that there were 19.43 per cent craftsmen in the city sample, compared to 19.20per cent in the census. Among the urban women in the sample, 14.36 per cent worked as “domestic servants,”compared to 15.42 per cent in the census. Then there were 10.63 per cent of the urban men in the samplewho were factory workers as compared to 12.39 per cent in the census. The figures for fishermen were 9.61per cent in the sample and 8.42 per cent in the census. For certain smaller groups there was certainly a greaterdeviation, especially with respect to figures for non-working, single adult women in various categories, butalso here the total size of each sub-group was small (Annex 3 in Socialstatistik (Social Statistics), vol. 1,Kristiania 1898–99).

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International Criticism, Domestic Defeat

The first encounters of the representative sampling method with the internationalstatistics institute (ISI) have already been described several times (Seng 1951; Kruskaland Mosteller 1980; Desrosières 1991 and 1998; Didier 2000), and I will refer to onlya few main points from the discussions. Kiaer presented the method for the first timeat the meeting in Bern, and here he occasionally encountered stinging criticism fromseveral prominent international statisticians.

In the Bern meeting, the first speakers to respond to Kiaer’s presentation of hismethod – supplemented with examples from the two studies referred to above – wereuniformly negative (ISI 1896). The German professor Georg von Mayr began with apointed warning against using Kiaer’s method. He argued that such “partial surveys”could have a certain value in relation to what was actually studied, but only in thisrespect. They could never replace complete censuses. Von Mayr had registered anincreasing tendency to use mathematics and advanced calculations in statistics, whichhe claimed occurred at the expense of observation. He was very much opposed tothis practice. However, this was a case of von Mayr blaming the baker for the poorwork of the smith: Kiaer had nothing to do with the increased penetration ofmathematics in the discipline of statistics. In none of his works did he use probabilitycalculation or even mathematics that were more advanced than calculatingpercentages, and when a mathematically formulated criticism was directed at him onhis home ground, it was quite clear that Kiaer was unable to address it.

The same kind of criticism was expressed by other ISI-members in 1895, andrepeated in 1897. It is actually not until the meeting in Budapest in 1901 that a newelement entered into the discussion. The Russian-German statistician and economistLadislaus von Bortkiewicz came up with a criticism that Kiaer did not respond to atall. He had studied an overview of the relationship between the “representativefigures” in Kiaer’s survey – the same that are presented in his lecture from 1897 andsubsequently published several times – and conducted a significance test developed byPoisson for cases such as this. Even though the numbers appeared to be close, thedeviations were too great to be attributed to chance, he explained. Von Bortkiewiczseems to have been positive towards Kiaer’s method, but made it clear that his figurescould not have come from a truly “representative method” (ISI 1903). In 1903 Kiaerfaced similar criticism, formulated in probability theoretical terms, from anotherstatistician. This meeting also showed no record of Kiaer responding to the criticism(ISI 1905).

At this point, however, Kiaer was placed in the middle of a heated debate inNorway regarding the disability statistics, a debate carried out in thick reports thatwere presented regularly from the involved parties, in discussions in the Economists’Association, and in lengthy and occasionally coarse commentaries in the newspapers.The first round of criticism came after the government had decided that the entiremajority recommendation from the parliamentary labor commission, and especiallyits statistical basis, should be reviewed by a specially appointed committee of experts,


quickly dubbed the “critique committee.” The criticism from one of the members ofthis board, mathematician and insurance specialist Jens Hjorth, was to become thebeginning of the end (of the beginning) of the representative method in Norway.

The outcome of the debate about Kiaer’s statistics cannot be understood outsidethe context of the political and professional controversies in which it occurred. Thepolitical aspect has already been discussed. The social insurance act was an expensivemeasure with an uncertain, but undoubtedly high, price tag. The Conservative Party(Høyre) opposed the measure, while the Liberal Party (Venstre) supported it. Themethod also ignited a professional controversy, and in a very special way. The actuarieshad long been a heterogeneous group, without a discipline of their own, and had longbeen without a voice in public life. When the Norwegian actuary association wasfounded in 1904, the actuaries had been for many years increasingly conspicuous asa conscious group with demands to be included when larger social schemes were tobe discussed. Their issue was the social insurance act report, where they ended up onthe same side as the critics of the proposal because, among other things, they believedthat the number of medically disabled (invalids) was strongly underestimated and thatthe scheme would be more expensive than expected.

The monopoly on expertise in the area of statistics lay in the Central Bureau ofStatistics. Here, social and economic issues were reported by people with legal, andin rare cases philological, expertise. But also when it came to welfare programs,which were undoubtedly close to the heart of the actuaries’ area of expertise, it wasKiaer and his men who were considered the foremost experts. When a proposal fora health insurance act was prepared in the 1880s, Boye Strøm was appointed amember of this committee, and Kiaer was a member of the parliamentary laborcommission. However, the actuaries were not given this opportunity – until thecompetent and self-confident Hjorth received a prime platform for advocacy by thegovernment in his participation in the critique committee.

Hjorth’s criticism can be divided into two main parts. First, he believed that aproper “insurance statistic” should be compiled by someone with expertise in thefield. Hjorth referred to the example of Germany, which had a disability insurancescheme for workers prepared by actuaries in principally the same way that privateinsurance companies operated. In studies such as the one Kiaer had attempted, theconcept of disability had to be defined with care so that people would understandthe questions and so that they could design a policy that would not disintegrate overtime. Thus the disability probabilities – i.e., the probability that a person in a certainoccupation and certain age group would become disabled – would have to bedetermined through observations taking place over a long period of time. The lack ofsuch long-term observations could be partially compensated by including retro-spective questions in the survey – although the survey asked only about occurrencesthat took place during the current year. But the value of such questions wascompletely dismissed by Hjorth. Among the examples he mentioned were thequestions about deaths in the family. Exact estimates of death were importantparticularly because disabled people who live a long time were (and are) exactly what

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actuaries and their companies fear the most. Reported deaths were included in thedistrict-wide calculations of disability probabilities. But Hjorth pointed out that adeath in the family was one of the most common reasons for moving, and that thesurvey did not ask whether the family had moved after the reported death. And inaddition to this potential source of error, Hjorth also pointed out that the informantsmust have remembered incorrectly because the reported deaths in the selectedhouseholds during the census years indicated total figures that lay far below those thatwere reported in the complete running statistics. What about the oral reports aboutthe extent to which the deceased had been a “pension-entitled invalid”? askedHjorth, and concluded that it was “virtually unthinkable” that one could achievereliable results without using observations over time.

Hjorth also suggested several times that it would be difficult to avoid thephenomenon of the actual existence of an insurance scheme having an effect ondisability figures. All of this indicated the necessity for having a generous safetymargin or using the German experiences and figures as a point of departure – withsimple adjustments to take into account the nationwide scope of Norway’s plan. Thiswas the approach that Hjorth found most favorable, but it resulted in completelydifferent costs: disability probabilities in Germany were about three times higher thanthose calculated in Norway (Hjorth 1902, 36).

The probability of disability in Norway was higher in the cities than in the country,it increased with age, and it was far higher among unmarried people than marriedpeople. This reflected the German experience. In his criticism of the survey, Hjorthpointed out that too few lists had been used in Christiania, and that unmarried peoplewere clearly underrepresented. This was particularly unfortunate because thedeviation between the sample and the population as a whole increased with therespondent’s age. What is remarkable is that Kiaer had already drawn attention to thispoint in the 1897 lecture and had received an explanation from the person in chargeof the practicalities, Eugene Hanssen, that the error was due to enumeratorsinterviewing too many people in relation to those who were on the lists to representthe township (Kiaer 1897, 15). This was corrected on a local basis by removing somelists, and to minimize complication, only unmarried men were removed so thathusbands and wives, who filled out a joint form, would not be split up.

Why on earth hadn’t Kiaer corrected this before the publication of the statistics andthe commission’s recommendation two years later? I posit that this is because theminiature model had such a great influence on selection. Kiaer did exactly not whatBoye Strøm had done, that is, “toss” questionnaires all over the country, only to latergroup them and weigh them together. He had put together a carefully constructed,exact miniature – this was his particular area of expertise – and then he developed aview of the whole afterwards through simple multiplication. This is why his researchdesign was so vulnerable to the miniature being interfered with by others.

Hjorth concluded his criticism by evaluating the representative sample inprobability theoretical terms. There is no question that in this respect his criticism had


some very valid points. The sample had not been compiled in relation to the subjectmatter at hand. When studying the risk of disability, the respondent’s occupation andthe socioeconomic categories in the population censuses should not be the selectioncriteria. At the very least, division should be based according to classification of risk.The category “workers,” for example, did not constitute a risk classification, as Hjorthpointed out. Factory workers and farm workers had completely different risk profiles(ibid., 17). Here Hjorth actually presages stratification based on characteristicsspecific to the individual study. This is based on a principle completely different fromconstructing a miniature picture from a population census, and it implies a furtherstep in the direction of the type of individualization or atomization mentioned in theintroduction.

With the methodology he selected, Hjorth also believed that he could demonstratethat the sample size was too small. He based his argument on disability probabilitiesthat were calculated for the separate age groups. This was not a question of largenumbers, especially for the younger age groups, but a few people could be expensivein the long run because not many people left the status of disabled after first acquiringit. In the statistical terms of the time, Hjorth calculated the “mean deviation” for thecalculated values. Then he determined the size each separate age group sample shouldhave been to have a 1/2 probability that pure chance did not produce a deviation ofmore than 10 per cent from the calculated figures. The number of respondents inKiaer’s groups constituted only a fraction of the figures Hjorth came up with.

Then Hjorth turned the question around: Given the estimates and sample sizes thatwere actually used in the study, how great could the “deviations” be expected to be?Here, Hjorth calculated from a specific age group with 16 disabled persons in asample of 3,606 people (0.444 percent) that one could deduce that the trueprobability lay between 0.22 and 0.66 per cent; that with a 2/3 probability laybetween 0.33 and 0.56 percent, and that with a 1/3 probability lay between 0.37 and0.52 per cent. Hjorth undertook similar calculations for the disability estimates forthe other age groups, with varying requirements for accuracy. Hjorth’s conclusionwas that the figures were more uncertain than the commission’s majority was awareof. But the actual procedure was far more interesting than the conclusion. WhatHjorth calculated is what statistical theory has later come to call “confidenceintervals.” When Hjorth wrote his recommendation (1900–02), however, suchintervals had not been used in connection with sampling surveys. The pioneer workin this respect is A. L. Bowley’s article from 1906, where the calculation of confidenceintervals (although he did not use this term) was connected to sampling surveys forthe first time through a mix of simple probability theory and stylized quantitativeexamples (Bowley 1906).6

6 As in the case of Hjorth, with Bowley it is a question of a practical adaptation of theoretical tools that weredeveloped by Laplace early in the nineteenth century (confidence limits). Neither Hjorth nor Bowleydeveloped any new, general theory.

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Kiaer, who in Bern was associated with mathematically inspired statistics bystatistical traditionalists, was now being assaulted from the opposite hold. There issomething tragic and ironic about the entire situation: Kiaer presented a method that,with some simple modifications, was later to become embraced by statisticians andwhose value and rationality was taken for granted. The attacks by the monographauthors are easy to understand in a greater historical context. But the irony lies in thefact that the most challenging, and for Kiaer the most devastating, criticism camefrom someone with a background and education that belonged to the “newgeneration.”

What did Hjorth really think about the method? His contemporaries perceived hiscriticism as an attack on the method as a whole, but I do not think this is a correctinterpretation. In his introduction, Hjorth describes the study as “successful in severalrespects,” and he doesn’t write anywhere that he is skeptical in principle of thesampling method. But when he criticized the statistics, he continually referred to“the representative statistics,” the “so-called representative survey,” etc. His criticismof the sampling and accuracy can also be read two ways: From a modern perspective,it is easy to interpret his criticism as being “internal,” that is, Hjorth accepted themethod but pointed out concrete weaknesses of a technical nature. Kiaer’scontemporaries probably understood little about what the criticism was founded on,but were well aware that an expert was highly critical of what had occurred.

After quite some time, the chairman and the secretary of the parliamentary laborcommission prepared a separate report that responded to the criticism where theystarted by saying that the critique committee and its public presentation had made thecommission’s statistical foundation look like “trash” (Konow and Hanssen 1906). Onhis own initiative, Kiaer issued a separate response (Kiaer 1903a).7 He clearlyperceived Hjorth’s criticism to be an attack on the very principles of his method anddefended it with familiar arguments. Then he addressed the claim that the variousgroups were not represented proportionately. On the one hand, he accused Hjorth ofbeing too concerned with inconsequential details, and on the other he admitted tocertain errors that had an overall effect of adding up to an under-representation ofdisability in the original figures. Kiaer also used a lot of ink discussing the differencesbetween Norway and Germany, and he strongly disagreed that it would have beenbetter to use German insurance statistics than to conduct a Norwegian study. InGermany, he claimed, there was a greater percentage of people living in cities,workplaces were more dangerous and less hygienic, people worked more often onSundays, and alcohol consumption was greater. On the other hand, he pointed out,Norwegians performed more “discontinuous work,” and “even the work that wasperformed regularly was not performed in a steady pace.” This way of working wasprobably more likely to result in disability, Kiaer believed. In this connection, he

7 See Kiaer to Konow, Sept. 1, 1902, Konow’s correspondence collection, Håndskriftsamlingen (Handwritingcollection), University Library.


brought up another type of over-exertion, namely that which was “associated withsports.” He wrote that “it cannot be denied that overexertion in this connection canall too often pave the way to an early occurrence of disability” (Kiaer 1903b, 56).

The quote above is taken from a lecture Kiaer held early in 1903. This lecture wasgiven while the media war was being waged between Hjorth and Kiaer, and Kiaer’sresponse had not yet been published. It is no surprise that neither Hjorth nor theother two members of the critique committee at the time attended this meeting,which took place in Kiaer’s home field, the Economists’ Association. In the time thatfollowed, the discussion more and more revolved around winning trust. For example,in one of his innumerable responses to Hjorth, Kiaer finished by saying that hecouldn’t deny himself the “satisfaction of concluding the present introductory piecewith a statement from a statistician and mathematician whose authority Mr. Hjorthwould not challenge, namely professor Harald Westergaard from Copenhagen. In aletter I recently received, he thanks me for, among other things, ‘sending thatwonderful material with respect to the Norwegian disability commission.’” Kiaerbelieved that mentioning these statements would be “quite beneficial” as a contrast to“those that have fallen from Mr. Hjorth’s pen.” 8 This is the closest he came toresponding to Hjorth’s more technical criticism, which was never touched uponexplicitly in his reports and newspaper commentaries.

I will not go into the political discussion about the proposed social insurance acthere, but the uncertainties regarding the costs and how to finance it, as well as thecontinual discussions about whether it should cover the whole working population,meant that the majority recommendation from Konow’s committee eventually lostweight and relevance. One of the critics of the proposal was Professor Oscar Jaeger,who was at the time becoming established as one of Norway’s most prominenteconomists. Jaeger was skeptical of the financial arrangements and of the fact that theinsurance would enter into force all at once and apply to all workers. But his maincriticism of the earlier report was that it was built on a completely inadequatestatistical foundation. He entitled a lecture delivered to the Economists’ Associationon February 26, 1906, “Should we take a second look at the proposed socialinsurance act?” Jens Hjorth was present that day, and he probably had an inkling ofwhat was coming. Jaeger’s lecture started out by attacking the statistical foundationupon which the previous report had been based. Jaeger claimed that the statistics wereprocured through a “so-called representative survey,” which was “uncertain” and had“a completely inadequate foundation.” Jaeger echoed Hjorth point by point in hiscriticism. And he did not neglect to give credit where it was due: Hjorth’s report wasdescribed as “masterful.”

8 Verdens Gang (daily newspaper), August 18, 1903. Hjorth published a long excerpt of his report inMorgenbladet in a series of articles through 1903. The debate between the two, however, was printed in VGthrough the summer and fall, after Kiaer allowed his first counter-argument to be published there. Hjorthhimself published his running contributions in Forsikringstidene.

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During the two-day discussion following the lecture, Kiaer got up and stated that“the number of disabled after more recent surveys unfortunately seems to liesomewhat at the higher end of the scale calculated by the parliamentary laborcommission.” By then, the Central Bureau of Statistics had already been conductingnew surveys of disability within certain occupational classes for quite some time. Theold estimates underestimated disability by a good thirty per cent, admitted Kiaer, whovolunteered the information on his own volition. No one had questioned himdirectly on this subject. Kiaer himself must have felt that providing the results of thenewer study was the right thing to do, even though he could hardly have chosen a lessopportune moment for himself (Jaeger 1906).

In Hjorth’s own recounting of events in the anniversary book from 1929, this wasthe most important day in the actuaries’ struggle for recognition (Faerden and Hjorth1929, 4). In his introduction, he dramatically tells the story of how the actuariesestablished their social standing and how it later became a profession with its ownindependent academic foundation. He starts by describing how the chair of theparliamentary labor commission, Wollert Konow, dismissed the actuaries’ expertise inthe parliament in 1902 by claiming it was irrelevant for evaluating the kind ofstatistical material that Kiaer had prepared. “An insurance technician is the craftsmanof the trade,” Konow is reported as saying. “He is the one that performs calculationson a given statistical foundation. But there is no one who says he is the right man toconstruct or discover the best design for an insurance scheme. Nor is it said that heis the right man to judge statistics” (ibid., introduction). Here Konow was referringto Hjorth’s report where Hjorth criticized Kiaer’s statistics. Hjorth then goes on todescribe the multitude of long discussions about Kiaer’s figures, where his criticismhad long been flatly rejected up until the deciding moment for him and otheractuaries on that winter day in 1906 when director Kiaer stood up at the Economists’Association and admitted that he had “unfortunately” been wrong the entire time. “Itwas quite a victory for the ‘insurance technicians’,” concludes Hjorth.

Hjorth also writes in the anniversary report that a new committee was appointeda year later with Jaeger as chair, Nicolai Rygg, himself, and later mathematicsProfessor Arnfinn Palmstrøm among the members. He tells that Kiaer also took partas the only representative of the previous committee, and he writes that the newcommittee would use completely different methods for finding out which reality adisability insurance scheme should be based on. But this governmental embrace ofthe actuaries and their methods is not given any independent justification in the book– none is needed in Hjorth’s account after the collapse of the opposition.

This ended the first sampling era in Norway. Well-informed readers will note thatthe method was in use also after 1906. In Norway there was a relatively large studyconducted in 1910, and two or three smaller studies in the years between the worldwars. As Bjerve (1983) points out, however, the latter have a scope and direction thatare difficult to compare with those conducted by Kiaer. But Kiaer didn’t plan anystudies after the criticism of the disability statistics began to win acceptance. The


income and asset study in 1910 was one of two larger studies that were planned longbeforehand. It was actually a follow-up to, and largely a copy of, the study from 1891.It was not controversial and was carried out without its methodology or results beingeither called into question or promoted in academic forums. The second large studywas ostensibly intended to bring the method further. It was to have been a large studyof alcohol consumption and its social impact. This study was mentioned by Kiaer inhis lectures as early as the late 1890s, and it was planned to be carried out early in the1900s. His thoughts about researching the correlation between alcohol and illness,criminality, divorce, deaths, and suicide through comprehensive sampling surveyscombined with a review of other state records, however, met with strong public andparliamentary resistance. After a series of “detailed descriptions” from Kiaer and hiscabinet minister about what should really be done, the sampling survey waseventually dropped, and the alcohol statistics were augmented by simply improvingthe coordination of information that would have been collected by the governmentin any case.9

There was no one who further developed the method after Kiaer. His successorNicolai Rygg expressed skepticism of the sampling method in his lectures at theuniversity. Rygg’s successor, Gunnar Jahn, wrote in the Norwegian BiographicalEncyclopedia that Kiaer’s most important contribution was using statistics to shine lighton social and economic conditions. “On a purely methodological and theoretical-statistical level, his contribution was smaller,” was Jahn’s judgment (Rygg 1912/13;Jahn 1936). To the extent that Jahn was aware of the representative sampling methodused while Kiaer was in office, he clearly perceived this as less interesting in atheoretical and methodological context.

So, why did it appear, and why did it disappear?

Why was the method developed in Norway? I have described certain social,institutional, and individual factors. In a European context, Norway had an advanceddemocratic constitution and lacked an influential upper class. Relative to mostEuropean countries, it can be said that Norway was egalitarian, and it was alsoethnically homogeneous. There was also a strong sense of nationalism, and in themid-1800s it increasingly became the “people themselves” who were considered tobe bearers of “Norwegian-ness.” These factors alone do not explain the genesis of asampling method, but they weaken the foundation for alternative ways ofgeneralizing and interpreting “representativeness.”

The institutional setting is also important. Within the statistical office, later theCentral Bureau of Statistics, the methodology development, statistical surveys and

9 See parliamentary recommendation, no. 59, 1909, pp. 379–395, document no. 15, 1909, Kiaer to the SocialCommittee, printed as an appendix to document no. 15, 1909.

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the needs of the governmental apparatus, ramifications, and instruments of powerwere all interconnected. The main question in Mohn’s first study could not have beenasked outside the governmental office. The questions in the cotter study could havebeen asked but not answered by others. In Strøm’s consumer study, the state wantedto know who used coffee, sugar, and petroleum. For this purpose, the state had astatistical office with researchers that had both an international orientation and anawareness of methodology. The state had lensmenn to distribute questionnaires, as wellas a postal service at its disposal to distribute the forms free of charge.

At the individual level – in both senses of the term – both Mohn and Kiaer hada typical individualistic approach to economic and social issues, even though onlyKiaer is discussed here in connection with his efforts to put an economic value onhuman life. At a general level, we can also find elements of this tradition in Sundt’sresearch. Here we find also an early combination of large-scale studies with regionaland social comparisons. All of these factors paved the way for the representativemethod. But it did not actually create it. Some credit must be given to the originator’s“intuition” and “courage,” as described by Seng.

And why did the method disappear? Kiaer came out of the struggle with themathematicians as the loser. The whole debate revolved around trust in his methodand came down to faith in him as a statistician and methodology expert. The generalpublic perceived his disability statistics as a fiasco, and it was hardly likely that therewere more than Kiaer and Hjorth who believed that the methodology and thestatistics could be evaluated independently of each other. If he did not acceptthe criticism, it became clear that he was not capable of arguing against people likevon Bortkiewicz and Hjorth. Kiaer became the subordinate, and it was not a positionthat suited him.

Kiaer touched upon the previously used method only one time after thecontroversies about the alcohol study in 1909. In the discussion after BredoMorgenstierne’s lecture “Good and bad statistics,” at the Economists’ Association inautumn 1911, Kiaer mentioned that it wasn’t always desirable to collect informationfrom a very large number of individuals in one single study because it could affectprecision. A smaller, but carefully selected data base was preferable. “If 6,000 differentpeople aimed for a target and threw projectiles at it by hand, it could happen that theaverage throw were close to the target, but this speaker would prefer 60 sharp-shooters” (Morgenstierne 1911). Kiaer didn’t name the representative samplingmethod explicitly, but there was little doubt about what he was aiming at.

Acknowledgments

I am grateful to Olav Bjerkholt, Silvana Patriarca, and Fredrik Thue for theircomments.


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Documents

The rise and fall of sampling surveys in Norway 1875-1906