What does all this mean for the purpose of this paper, namely, testing the U-shaped economic orientation of the standard narrative on economic sociology? At least three things:
(1) We need to keep distinct what people in the new economic sociology believe to be an economic issue (call this economic-as-in-new-economic-sociology, or economic-nes) from what the topic model measures, and we interpret, to be an economic issue(s), (call it, economic-as-in-topic-model, or shorthand, economic-tp, work-labor-tp, and organization-tp).
The topic model does not capture all the nuances of a language, a theory, or a discipline. It is a tool to aid us order and quantify a certain corpus. This means that even if two different research disciplines define themselves in opposition to each other but work on exactly the same topics, the topic model we are employing 16 will find them to belong to the same topic-mix. However, this is also the advantage of our topic model, namely that it will capture what people actually write about regardless of disciplinary membership. This allows us to discover economic topics and orientation inductively, which is our focus since we are agnostic about disciplinary memberships. In that we follow, “[…] Jacob Viner’s little phrase about economics, we should perhaps simply and modestly say that today economic sociology is what economic sociologists do" (Fourcade 2007: 1018).
(2) We need to construct a proxy(s) in order to be able to measure and to conduct a formal statistical test of the trending of the classical and the new economic sociology for the period 1890 to 2014. What we have shown in the three analysis steps above, that economic-nes and organization-tp fits strongly; moreover, that the average new economic sociologists have a topic-mix of both a high portion of the organization-tp and another portion of the social-theory-tp. The classics have a topic-mix concentrated to social-social-theory-tp. Consequently, we will construct a proxy that calculates the sum of the organization-tp and social-theory-tp for each article, for the whole sample; we will then use this proxy to analyze the trending of both the classical and the economic sociology.
16 See supervised machine learning or sentiment analysis for a wider family of algorithms.
25 (3) We have in the validation step discovered that there is merely a weak fit between economic-nes, on the one hand, and the economic-tp as well as the work-labor-tp on the other hand. We have demonstrated that this is an actual feature of the population and not a validity issue. Neither the classics nor the new economic sociologists contribute much to the economic-tp and work-labor-tp. Nevertheless, since economic-tp might prove to be a third type of sociologists being interested in economic issues but with no explicit disciplinary membership in the new economic sociology (viz. the political economists), we will depict the trending of this proxy as well.
From the account above and in order to test the U-shaped economic orientation of sociology of the standard narrative we articulated the following hypotheses:
1. During the era of 1890 to 1920 there is a high level of economic orientation in sociology (intercept) with an increasing trend (positive slope). This is the Era of the Classics.
2. During the period 1921 to 1985 there is a lower level of economic orientation in sociology (intercept; lower than the classical era) with a decreasing trend (negative slope). This is the Dormant Era.
3. During the period 1986 to 2014 there is a higher level of economic orientation (intercept; higher than the Dormant Era) with an increasing trend (positive slope). This cut point marks the seminal publication of Mark Granovetter´s (1985) Economic Action and Social Structure – the problem of embeddedness.
The standard narrative gives us merely some anecdotic cut-points regarding when we should expect a rise and fall in the economic orientation of sociology. In order to depict the exact historical trending of these various topics we also ask:
4. What year(s) does the organization-tp + social-theory-tp topic reach its peak (maximum) and bottom (minimum)?
5. What year(s) do the economic-tp and work-labor-tp topics reach their peaks (maximum) and bottoms (minimum), respectively?
Lastly, several sociological journals are explicitly oriented towards economic issues. Some are not in our sample (e.g. Socio-Economic Review), others are (e.g. the American Journal of Economics and Sociology). Therefore, it is relevant to know which of the journals in our sample contribute more or less than the average to the overall economic orientation of sociology:
6. What are the journal contributions to the overall economic orientation of sociology?
26 4.3The multilevel modeling: analyzing the time-trend of the economic
orientation of sociology over the last 124 years.
The multilevel models yield the following results for the economic and the organization/social-theory topics as dependent variable:
Table 4: Multilevel Regressions for the Economic and the Organization/Social-Theory topics
27 Table 4 outlines the multilevel regression analysis. In table2 in Table 4, we conduct all the tests regarding the trending of the combined measure of the organization and social theory topics. In model1 we decompose the variance into the between-journal (RP2.var.Intercept) and the within-journal variation (RP1.var.Intercept). This model shows where we have 36.6%
of the variation between journals and the rest within them (between-articles in the same journal). This model has a superior log-Likelihood 587256.19) over a single level model (-618039) (not shown in the table). This variation defines how much of the differences with regard to the combined organization and social theory measure is due to differences between the journal-level versus the article-level. Any journal variable can thus at a maximum explain 36.6 %, whereas any article variable can explain that as well as the remaining 73.4%. Journal variable examples are: the editors, the editorial board, the publisher, the journal affiliation.
Journal variables are characteristics of the journal that apply to every article within the journal. Article level variables are: publication date, authors´ characteristics (e.g. gender, age, affiliation, funding), page length, citation, and other bibliometric characteristics. In this study, besides the time (publication date) variables, we will only use the page length of an article as a covariate since we lack other readily available features in the JSTOR data (such as the gender of the author, institution, funding, title of the author etc.).
In model2 and model3 we test the conventional story of the U-shaped economic orientation of the discipline of sociology. In model2 we estimate the average level of organization and social theory orientation. We can already here see that for this combined topic-mix, sociologists were as economically (viz. economic-as-in-new-economic-sociology) oriented today as they were about 70 years ago, but more so as they were 100 years ago. On average, during the classical era, between the period 1890 to 1920, a random sociology article had 5.64 % of organization/social-theory topic-mix. During the intermediary era, between 1921 to 1985, this topic mix was 17.17 % on average. During the new economic sociology era, between 1985 and onwards, this topic-mix rose to 17.47 % - but not significantly different from the hiatus era. These observations do not support the conventional story.
Another way of viewing the same thing is captured by model3, which now included the trends within each era. During the very beginning of the classical era (around the year 1890), the average sociology article had a 12.84 % of the organization/social-theory topic mix. The trend within this era was (Era1890to1920slp), however, decreasing by 0.36 % topic mix by every year. During the start of the intermediary era, the average sociology article is estimated to have 5.17 % of this topic-mix. The trend (Era1921to1985slp), however, was increasing with about 0.25 % by every year. This led to an average estimated topic mix of 20.50 % at the beginning of the new economic sociology era. Observe, now that during this era the trend (Era1986to2014slp) is decreasing again by -0.15 % every year. Neither does this model support the conventional story. 17
17 We tested also for an explicit Within-Between Random Effect estimation as suggested by Bell and Jones. We
find little evidence for a between-effect with regards to this time variables. This means that we are getting a
28 The two previous models were constrained to test the level and the trend of a particular story, with three cut-points. In model4 through model7 we fit various polynomial models to the data in order to assess the best functional form of the trend more freely. Comparing the log-Likelihood of these four models, we can see that model6 (a third degree polynomial function) has the best fit to the data: 1169464.88. A fourth degree polynomial function does not significantly improve the fit. Figure 4 captures the estimated trend of model6. This graph tells us that there the bottom of the Organization/Social-Theory topic mix occurred in 1929 and that the peak occurred by 1989. 18 After that, we have entered a period of stagnation or even depression – only future data will tell if this is merely a temporary glitch or a permanent trend.
precise fixed-effect estimator. Using a random effect model instead of a fixed effect model allows us to estimate the within-effect but also estimate the between-journal variance.
18 It should be mentioned that we fitted the same polynomial models as in model4 through model7 but by letting
more slopes vary. Some of these models do improve the fit (log-Likelihood and DIC), but result often in model
non-convergence – most likely due to the unbalanced nature of the data. However, these models point to the fact
that the maxima was reached by year 2002. However, some of them estimate that the peak occurred in 1926. The
difference between having two or one random term can be seen as a way of adjusting for outliers with regards to
the general trend of the discipline of sociology. This also means that having 2 random terms will capture an ever
more nuance in the deviations for when various journals had their peak and bottom by a fraction of couple of
years only.
29
Figure 4: Trends of the Organization/Social-Theory topic mix
We turn now to the trend of the Economic topic, which is captured in table1 in Table 4.
Model1 partitions the between-journal and within-journal variance. For the Economic topic,
we have 37.7 % at the journal level, which is similar to the Organization/Social-Theory topic
mix variation. This model also shows that a multilevel model is superior to a single level
model. Model2 shows that the discipline of sociology had on average 13.46 % Economic
topic orientation; 6.66 % during the hiatus era; and somewhat less during the new economic
sociology era, 5.71%. Model3 shows that by the beginning of the classical period, a random
sociology article had 7.75 % orientation towards this topic and increasing by 0.29 % every
year until the end of this period, to 1920. By now the average article had 12.92 % but with a
decreasing trend until 1985. After the publication of Granovetter´s article, the trend was still
decreasing, albeit shallower (-0.07 %). If we had any doubt that the conventional story could
be supported by analyzing the Economic topic instead of the Organization/Social-Theory
topic mix, this account shows even the reversed picture. The discipline of sociology is going
towards a decrease with reference to contributing to this topic as well.
30 Similarly, to the Organization/Social-Theory topic mix, we can estimate, a model that captures the actual trend: done in model4 through model7. For the Economic topic, a fourth degree polynomial presents the best fit. 19 Its result is depicted in Figure 5. This figure shows that the sociology discipline reached a peak already by 1923 and has been in a decreasing trend since. The model estimates a slow-down in this depreciation around the period between 1970 and 1990; with a further acceleration of the depreciation after this period.
Figure 5: The trend of the Economic topic
19 A fifth degree polynomial results in a worse fit with a log-Likelihood of -584718.1.
31 4.3.1Journal rankings
Figure 6 depicts and ranks the level of economic topic orientation in 143 journals; as estimated in model 7. The conditional average (intercept) estimates that a random article has about 0 % economic orientation (the -1.14 is not significant) by the year 1890 20 ; a central question is what journals (clustering of articles) are driving this effect, that is which journals have an above average or below average economic orientation.
Figure 6: Journal ranking of the growth of the Economic topic
20 To be more correct, for an average paged article of 20, the average random article has about 1% of Economic
topic orientation: 20 multiplied by the Pagelength parameter of 0.05.
32 Figure 6 shows that some specialized journals rank highest, as: Acta Turistica, Social Scientist, Rivista Internazionale di Scienze Sociali. Followed by more familiar journals such as Work, Employment, and Society, American Journal of Economic and Sociology, Review of Social Economy, which all score significantly higher than the average level of Economic topic orientation 0 %. The generalist journals the American Sociological Review scores significantly below this level (a couple of percentage points); whereas American Journal of Sociology is barely non-significant. Análise Social, Journal of Educational Sociology, and Social Problems have the lowest Economic topic orientation.
Figure 6 shows the distribution (ranking) of how much journals deviate from the estimated negative growth rate of -0.73 in model 7. Some of the journals that had less than average economic orientation also have had a less step average negative growth rate in economic orientation: 1 st Análise Social, 2 nd Journal of Educational Sociology, and 6 th Social Problems (non-significant). Acta Turistica, that had the highest level of economic orientation is also the one with the steepest negative growth rate. This reversed correlation between the level (the intercept) and the growth rate (the slope) is a general trend in the data and is captured by the negative covariance of -1.72 (the parameter RP2.cov.Intercept.Years in model7).
The equivalent ranking has been calculated for the Organization/Social-Theory topic mix. The journal distribution is more varied compared to the Economic topic: more journals situating themselves above or below the average trend. The starting value is estimated to 25.56 %.
Sociological Theory ranks first and has about a 80 % higher orientation on the Organization/Social-Theory topic mix, whereas the German based Historische Sozialforschung scores equally high, of about 70 % lower, but now on the other side of the scale. The American Journal of Economics and Sociology and Review of Social Economy now score somewhat below the average trend for this particular topic mix. Interestingly, The Academy of Management Journal – an explicitly organization research journal – scores below the average by 1890.
However, this same management journal, accompanied by other competitors as The Academy of Management Review, Administrative Science Quarterly have had a high above-average rise to orient themselves towards organization and social theory research. Thus, even if the general trend is negative for the Years parameter (-0.73), these journals have a positive growth rate.
The covariance between the initial orientation (the intercept) and the growth rate of the journals (the slope), is negative (-7.34). This portrays a similar relationship as for the Economic topic, journals having less than average starting values tend to have higher than average growth. What this indicates is that journals are becoming more similar over time.
5Discussion and Conclusions
To best of our knowledge, there exists to date no sociological research contribution that uses
the amount of information that we have assembled in this article: all JSTOR sociology
full-33 text articles between 1890 to 2014. We have used this information to contribute to our self-understanding as sociologists and as a discipline; about its disciplinary history and its economic orientation. We started out with the standard narrative about the historic development of economic sociology: economic topics within sociology are said to take a U-shaped curve over the last century with the bottom in the post- war era and Granovetter’s article as a main promoter of these topics. We found that, contrary to that narrative, the strictly economic topic in our corpus has had only an initial peak and has been in decline ever since, while the mix of organization- and social-theory-topic – the one most realized in texts of the New Economic Sociologists – follows indeed a U-shaped curve, but with a much much underway. We discovered that the trend for the Organization/Social-Theory topic mix reached its bottom by the year 1929 and then that that this trend peaked again by the year 1989. This peak is an all-time-high for the discipline of sociology. Nevertheless, after 1989 and even after the Great Recession of 2007, this trend has been steadily decreasing.
One main thrust of our paper is thus to show that the self-understanding of economic sociology is in conflict with the actual prevalence of economic topics as found by our analysis which sticks closer to what sociologists actually do instead what they claim they do. The dearth in economic topics reported in the standard narrative for the pre-1980 period has been dismantled by our empirical analysis and can be considered a founding myth of economic sociology. Previous sociology had talked about economic phenomena, even if it might be true that they did not do so under one coherent heading or movement. It might also still hold that while sociologists, in practice, talked about the economy, dominant theories did not attribute much importance to economic elements in their theories (Baurmann 2001: 380).
As it turns out, what economic sociology itself would consider as some core texts and authors of their discipline are actually much more pervaded by other dominant themes than economic ones. Thus, the strong presence of organization topics inheriting from neo-institutionalism, of quantitative topics inheriting from network analysis and of social theory inheriting from post-Parsonian debates show both the heterogeneity of approaches in economic sociology, but also its roots in traditionally other topic areas. On average, a new economic sociologist contributes about 10% to the Economic topic, whilst he or she contributes 21 % to the Organization topic 21 and 28 % to the Social Theory topic. At the same time, empirical articles in a broad political-economy current constitute the main thrust of the Economic Topic in our topic model.
21 Organizational sociology became a booming field ever since WWII (Scott 2004), differentiated itself from
other fields and concentrated into a field with own journals, professional groups (Augier, March, and Sullivan
2005).
34 The findings of this study are confined, of course, by the data limitations which we initially mentioned: English-centeredness, selective journals and no books. All of these limitations can in principle be overcome in future studies. Other article-providing platforms such as Ebsco can be used to complement the JSTOR data; individual journals and additional volumes can be added to the corpus to see whether this changes any of the results. Book reviews published in journals can offer first insights into the topics of the reviewed books and the ongoing digitalization of ever more sociology books will also make it possible to extend the journal corpus into the book area. The study can in principle be replicated for other languages as well although the mix of several languages within one topic-model is problematic.
What concerns the explanatory side, more meta-data can be extracted from the text data or
even joined from other external sources to add more control and explanatory variables into the
model. This offers a virtually unexploited field of future research, linking precise topics with
collaboration networks, university affiliations , researchers’ careers , etc. Much work done in
bibliometrics on the basis of titles or abstracts only can now be refined by a larger basis of
What concerns the explanatory side, more meta-data can be extracted from the text data or
even joined from other external sources to add more control and explanatory variables into the
model. This offers a virtually unexploited field of future research, linking precise topics with
collaboration networks, university affiliations , researchers’ careers , etc. Much work done in
bibliometrics on the basis of titles or abstracts only can now be refined by a larger basis of
