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Historical informatics
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On the Possibility of Using Geoinformation Technologies to Study Economic Inequality (Based on the Materials of the Siberian Region of 1926-1927)

Vladimirov Vladimir Nikolayevich

Doctor of History

Professor, Department of Russian History, Altai State University

656049, Russia, Altai Krai, Barnaul, Lenin Avenue, 61, room 312

vvladimirov@icloud.com
Other publications by this author
 

 
Krupochkin Evgenii Petrovich

PhD in Geography

Associate Professor, Head of the Department of Economic Geography and Cartography, Altai State University 

656049, Russia, Altaiskii krai, g. Barnaul, ul. Prospekt Lenina, 61, aud. 502M

krupochkin@mail.ru
Other publications by this author
 

 

DOI:

10.7256/2585-7797.2022.4.39387

EDN:

ZRZMLZ

Received:

13-12-2022


Published:

30-12-2022


Abstract: The article discusses the possibilities of using geoinformation technologies to study economic inequality. The methodology and technique of applying geospatial analysis in the study of wage inequality of employees of district cities of the Siberian Territory in 1926-1927 are shown. Statistical bulletins published in 1926-1929 in Novosibirsk were used as sources. Data were selected that characterize the salaries of employees of the district cities of Siberia for 8 quarters, covering almost 2 years – 1926 and 1927. During the development of GIS, a 1:3000000 scale map of the Siberian Region was digitized, on which there is a coordinate grid, the situation (hydrographic network and relief displayed by washing) and administrative division were plotted according to the zoning data of 1929. A series of maps was built reflecting the average salary level of employees in district cities, as well as the dynamics of wages based on quarterly statistics. The highest salary of employees is observed in Novosibirsk. It is noticeable that cities with low wages are concentrated in the south of Western Siberia. The growth rates of wages in cities show a greater variation than the average salary. The largest increase in wages is demonstrated by those cities in which its level was low or average. It can be stated that there are certain prospects in the use of geoinformation technologies to study economic inequality.


Keywords:

GIS, geoinformation technology, economic inequality, Sibirsky krai, source, city, employee, wages, map, differentiation

This article is automatically translated.

IntroductionThe study of various aspects of economic inequality in the past is one of the leading trends in economic history.

The interest in this is due not only to the possible projections of the developed provisions and formulated conclusions to the present, but also to the quite achievable prospects for obtaining reliable and verifiable historical knowledge based on a wide range of statistical sources and a solid methodological base involving mathematical methods and information technologies.

Meanwhile, geoinformation systems and technologies, the popularity and effectiveness of which in historical research has reached a very high level, have not yet become a familiar tool for studying historical aspects of inequality. At the same time, the study of such one of the types of economic inequality in our country – wage inequality – inevitably faces the problem of regional peculiarities in the vast territory of Russia, where the specifics of natural-geographical and socio-economic conditions have determined the specifics of socio-economic processes.

As a result, there should be access to the spatial features of the regions and their influence on the specifics of the processes taking place in a particular territory. Thus, the possibility of using geoinformation technologies in this case can be said a priori. This paper discusses some aspects of the application of geospatial analysis in the study of wage inequality among employees of district cities of the Siberian Territory in 1926-1927 (the period of the late NEP).

Sources and methodologyThe Siberian Region was formed on May 25, 1925 by the decree of the Presidium of the Central Executive Committee [1].

As a result of the enlargement of the administrative-territorial division, a giant region appeared, which included 6 provinces and an autonomous region. The capital was the city of Novonikolaevsk (since 1926 – Novosibirsk). At the same time, the formation of the system of state statistics took place [2; 3; 4]. The regional statistical bureau was launched, and later the regional statistical department. Powerful statistical forces consisting of high-level practical statisticians were concentrated in the regional center. They published, in particular, various statistical collections, including a series of publications "Bulletin of Labor Statistics of the Siberian Region" (1926-1928) and its continuation "Bulletin of Labor and Industry Statistics" (1928-1929).

It is clear that not all statistical data are suitable for working with them in geoinformation systems. A necessary condition here is their binding to certain spatial units, which may be administrative-territorial territories. From this point of view, we have selected data that characterize the salaries of employees of the district cities of Siberia for 8 quarters, covering almost 2 years – 1926 and 1927.

Based on the available data, a table was created in Microsoft Excel for further processing. Some adjustments have been made to the table. Thus, the cities of Tulun and Kirensk, for which data were provided only for part of the period, were excluded from the table. In the list of cities, along with Barabinsk, Kainsk is indicated, which was not the center of the district, but in most cases wages are indicated in it, although the center of the district was Barabinsk. The missing Biysk salary value for February 1927 was restored as the average value between the wages of two adjacent periods (Table 1).

To create thematic maps and further analyze spatial patterns, we calculated the average wage values for the period under review, as well as the growth rate, both of these indicators were added to the table. The growth rate is based on the formula: where ?P is the growth rate, Pt is the current period (the most recent data in chronological order), Pb is the value of the indicator for the previous or base period of statistical observation.

 

 Table 1

 

Salaries of employees in the cities of Siberia in 1926-1927 . (in gold rubles)

Cities

 

 

 

 

 

 

 

 

 

 

 

February 1926

May 1926

august 1926

november 1926

february 1927

May 1927

August 1927

November 1927

Average value

Growth rate

 

 

 

 

 

 

 

 

 

 

 

Container

45,07

46,24

52,94

55,59

52,54

58,00

60,65

59,56

53,82

32,15%

Omsk

61,68

59,67

59,36

61,10

69,93

67,50

63,30

62,56

63,14

1,43%

Kainsk/Barabinsk

49,39

54,86

59,05

61,77

61,94

72,53

64,39

69,30

61,65

40,31%

Slavgorod

45,82

48,96

52,13

57,93

59,37

59,25

58,94

74,08

57,06

61,68%

Stone

42,02

46,20

51,48

55,26

54,60

61,02

58,64

62,40

53,95

48,50%

Novosibirsk

73,22

74,14

74,05

77,86

78,05

80,24

80,92

82,51

77,62

12,69%

Barnaul

49,51

50,26

52,51

52,78

53,44

62,08

52,91

54,66

53,52

10,40%

Rubtsovsk

51,66

54,99

55,75

58,12

58,06

61,92

62,73

65,33

58,57

26,46%

Biysk

49,77

47,58

46,88

51,18

51,51

51,84

55,11

55,83

51,21

12,18%

Ulala

55,75

58,98

59,03

62,62

73,47

71,34

68,54

68,28

64,75

22,48%

Tomsk

55,30

55,60

53,29

59,18

60,01

60,61

59,90

61,91

58,23

11,95%

Achinsk

41,99

51,86

59,75

62,27

61,12

68,32

60,81

62,92

58,63

49,85%

Krasnoyarsk

50,85

50,02

53,23

56,22

57,08

57,46

57,40

60,66

55,37

19,29%

Shcheglovsk

47,89

65,99

59,10

64,75

57,80

54,28

52,43

71,56

59,23

49,43%

Ust-Abakansk

48,26

53,38

53,63

53,53

59,21

63,27

64,68

64,99

57,62

34,67%

Minusinsk

49,19

49,54

49,77

51,57

53,52

54,36

57,15

60,02

53,14

22,02%

Kansk

51,14

54,61

51,07

55,43

55,56

55,28

57,44

57,68

54,78

12,79%

Irkutsk

50,46

52,98

53,58

56,34

57,54

58,71

60,23

64,11

56,74

27,05%

 

Sources: [5, p. 41, table. 12; 6, p. 22, tab. 12; 7, p. 31, table 18; 8, p. 39, table. 17; 9, p. 26, Table 15].

 

To develop historical GIS and further data visualization using its tools, as well as geospatial analysis of various aspects of inequality of the population of the Siberian Region, operations were performed to create a set of spatial historical data, as well as geocoding of statistical information, GIS functionality was applied for geostatistical processing and analysis of the results obtained.

 

 

Fig. 1. Publication of the map of the Siberian Region used for digitization in GIS.

Source: [10].

 

During the development of GIS, a 1:3000000 scale map of the Siberian Region was digitized (Fig. 1), on which there is a coordinate grid, the situation (hydrographic network and relief displayed by washing) and the administrative division according to the zoning data of 1929 were plotted (Fig. 2).

 

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Fig. 2. Map of the Siberian Region: compiled by V.G. Boldyrev.

Source: [10]

 

Special attention was paid to the mathematical basis. A modern reference point is taken as the origin of the reference system/coordinate system – the intersection of the Greenwich meridian line with the equator line. It is indicated on the map that its main scale is preserved at the 50th and 60th parallels of the S.S., this indicates the use of a conical projection, but we did not have the exact parameters of this projection.

The tasks preceding the entire cycle of work on the creation of historical GIS were the transformation and geo-linking of the specified map. Transformation is a procedure of geographical reference and geometric correction of an image (raster), in which not only the creation of a mathematical basis occurs, but also the elimination of distortions on the map (raster) by performing mathematical transformations. The full cycle of geo-linking operations in the case of minor distortions on maps is described by us in the previously published article [11].

However, for our card, in fact, this procedure was performed twice:

1. When converting a raster using the spline method in ArcGIS;

2. When importing the transformed raster and georeferencing in MapInfo PRO.

To perform the transformation, a sufficient number of links is required, provided that the raster (map) corresponds to the coordinates of the target data. To achieve the maximum coincidence of coordinates, a coordinate grid layer created with a step of 2 degrees is used. To transform raster data, we used the spline method with the following parameters:

 

X’ = Ax + By + C,

Y’ = Dx + Ex + F,

 

where X is the number of columns in the raster, Y is the number of rows, X’ is the horizontal value in coordinate space, Y’ is the vertical value in coordinate space, A is the width of the cell in map units, B is rotation, C is the x’ coordinate of the center of the upper left cell, D is rotation, E – negative height of the cell in map units, F – y' coordinate of the upper left cell (Fig. 3).

 

 

Fig. 3. The scheme of raster transformation using mathematical transformations

Source: [12].

 

Thus, six key parameters determine the transformation of the raster into a given coordinate system and projection – A, B, C, D, E, F. The final stage was the import and re-correction of the raster at the nodes of the coordinate grid (Fig. 4).

 

Èçîáðàæåíèå âûãëÿäèò êàê êàðòà  Àâòîìàòè÷åñêè ñîçäàííîå îïèñàíèå

 

Fig. 4. The scheme of binding and correction of the imported raster in the MapInfo PRO program

 

The completed cycle of operations minimizes distortion across the map field and allows you to work with it in a GIS environment. Let's note the main advantages of the processed and geo-linked raster:

1. Digitization in a given coordinate system;

2. The possibility of using any cartometric operations and functions provided by the GIS functionality for working with spatial data;

3. The possibility of correct layout;

4. The ability to perform overlay operations;

5. Analytical operations.

 

When digitizing the boundaries of the districts, we used a geo-linked historical map of the Siberian Territory published in 1929, which no longer had the Tarsky District, the entire territory was part of the Omsk District. Therefore, first, natural and administrative landmarks (internal division, river network) were determined, and then the border between Omsk and Tarsky districts was already drawn along them.

The next step was geocoding the database from the Microsoft Excel environment into GIS. Geocoding refers to the process of displaying external or internal (data in the system) spatially coordinated data on the map, or the process of converting a location description (for example, coordinates, address or place name) to a location on the Earth's surface [13; 14].

The digitization of the districts was carried out taking into account the topology of the map and layers, in which the topological (or geometric) relations between the common parts of objects for all objects within the layer have an equivalent value. This allows you to edit objects with a common geometry at the same time. When creating topologically correct objects, individual sections were traced when they coincided with the layer of modern administrative division. This approach, firstly, saves time on digitization, and secondly, increases the accuracy of the location of objects plotted on the map in the plan.

The next stage (geospatial historical analysis) consisted in constructing a series of maps reflecting the average salary level of employees in district cities, as well as the dynamics of wages based on quarterly statistics (Table 1). As an indicator of dynamics, we used the growth rate. At the same time, for the convenience and clarity of visualization, we considered it possible to distribute data on the cities – the centers of the districts – to the entire territory of the districts. Thus, when analyzing cartograms, it should be borne in mind that we are not talking about districts as a whole, but only about their centers.

Main resultsTo visualize the distribution of statistical indicators, both absolute (initial) and relative, we used discrete methods of constructing thematic maps in a GIS environment.

They are represented by classical cartograms built on a grid of districts and displaying the corresponding statistical indicators for two years – 1926 and 1927.

Visualization of average salary values by city (Fig. 5) shows that the highest salary of employees is observed in Novosibirsk, which is not surprising, since it is the capital of the Siberian Region.

 

 

Fig. 5. Distribution of average wages in the district cities of the Siberian Territory in 1926-27 (in gold rubles)

 

By expert means, we have identified the intervals of wages shown on the map in the district cities corresponding to low (up to 56.0 rubles), medium (from 56.1 to 60.0 rubles) and high (from 60.1 to 70.0 rubles). her level. Novosibirsk, where the salary is the highest (77.62 rubles), we considered to allocate it to a separate group as the center of the Siberian Region.

 

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Fig. 6. Cartogram of the average salary of employees of district cities of Siberia by districts of the Siberian Territory in 1926-1927. On the cartogram (Fig. 6), it is noticeable that cities with low wages are concentrated in the south of Western Siberia (Barnaul, Biysk, Kamen), this also includes Tara and a number of cities in the central part of the Siberian Territory (Krasnoyarsk, Kansk, Minusinsk).

Cities with an average salary level are located in Eastern Siberia (Irkutsk) and Western Siberia (from Tomsk in the north to Ust-Abakansk in the south), they also include the cities of modern Altai Krai Slavgorod and Rubtsovsk. The high level of wages characterizes two cities in Western Siberia (Kainsk, Omsk) and the center of the Oirot Autonomous Region of Ulalu, which at that time was just becoming a city. Given the geographical location of Novosibirsk, we can talk about a high differentiation of intercity salaries of employees in the district cities of Western Siberia.

Visualization of salary growth rates by city (Fig. 7) shows a greater variation than the average salary. There are more or less three groups of cities with low (up to 13.0%), medium (from 13.1 to 40.0% and high (over 40%) growth.

 

 

Fig. 7. Distribution of the average wage growth rate of employees in the district cities of the Siberian Territory in 1926-27 (in %)

 

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Fig. 8. Cartogram of the growth rate of average wages of employees of district cities of Siberia in the districts of the Siberian Territory in 1926-1927.

 

On the cartogram (Fig. 8) it is clearly noticeable that the greatest increase in wages is demonstrated by those cities in which its level was low (Kamen) or medium (Slavgorod, which is the leader of the increase, Shcheglovsk and Achinsk), and sometimes even high (Kainsk). All these cities, with the exception of Achinsk, are located in Western Siberia. The smallest increase is observed, on the one hand, in cities with high salaries (Novosibirsk, Omsk). But this also includes a number of cities with low wages, the lack of growth of which leads to the allocation of peculiar "outsider cities" in this regard (Barnaul, Biysk, Kansk). Thus, in the district cities of Western Siberia, there is a further inter-city differentiation of employees' salaries.

ConclusionThe given examples of the use of geoinformation technologies show that there are certain prospects in their use for the study of economic inequality.

For further development of this direction, it is necessary to expand the source base and improve the methodology and technique of research.

References
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Review of the article "On the possibility of using geoinformation technologies to study economic inequality (based on the materials of the Siberian Territory of 1926-1927)" The reviewed article is devoted to the consideration of the possibilities of using geoinformation technologies and statistical methods to study economic inequality and has a methodological character. The problem is presented and solved on the basis of statistical materials on the salaries of employees of the district cities of the Siberian Territory in 1926-1927. The methodology of the article is based on a spatial approach to the study of historical phenomena and processes. Geoinformation systems (GIS) and geoinformation technologies are used to implement this approach. The map of the Siberian Region of 1929, prepared and processed for use in GIS, was used as a base map. Statistical arrays formed on the basis of representative sources – "Bulletins of labor (and industry) statistics", published in the second half of the 1920s in Novosibirsk, are taken as attributive data. The relevance of the article is determined both by general considerations – the digital turn taking place in historical science, as a result of which mathematical methods and digital technologies are being introduced into the methodological base and methodological apparatus of scientific research, and by specific considerations consisting in the implementation of new ways of extracting information from historical sources. The scientific novelty of the article is due, on the one hand, to the involvement of new source material, on the other, to the use of modern data analysis tools. As part of the study, both statistical and spatial data were processed. The article has a clear structure, reflected in the division of the presented material into sections. The introduction raises the problem and substantiates the possibility of using geospatial analysis to study the processes of economic inequality based on materials on salaries of employees of the Siberian Territory. Next, the sources are characterized and methodological issues related to the creation of a geospatial environment for further data analysis are considered. A detailed description of the statistical data summarized in the table is also provided. Based on these data, a historical geospatial analysis is performed, consisting in the creation of thematic maps. One of them reflects the distribution of average wages for 1926-1927, the second – its increase over the period under review. The created thematic maps allowed us to draw several important conclusions, indicating, among other things, the prospects of using geoinformation technologies in the study of economic inequality. The article is written in an academic style in good scientific language. The bibliography of the article contains a small number of relevant works, including sources and manuals on geoinformation analysis, which fully reflects the methodological orientation of the article as a whole. The article does not raise controversial issues, again due to its methodological nature. The main focus is on GIS technologies and the analysis carried out with their help. In general, the article is of interest both for specialists in the field of economic history, researchers of economic inequality, as well as for historians who use geoinformation technologies in their research. The article fully corresponds to the format of the journal "Historical Informatics" and, of course, will find its reader. The article is recommended for publication.