This page gives an example of how the database could be utilized for making visualizations.
Estimating with Limited Data: Labor Efficiency in 1843
One way for thinking about working conditions, without having a specific amount of workers per factory, is to analyze the efficiency of the factory (often researchers with more data will calculate the number of looms or spindles per worker). With utilizing the 1843 data, comparing the amount of hours that a factory operated (or that workers labored) with the the total cotton produced demonstrates the efficiency of production and conditions under which laborers were expected to work. One research question would be: was there a large distribution of cotton spun by the factory per hour worked, and how did this vary per region? The following graph shows the amount of cotton produced in pounds versus the amount of hours worked. The only includes spinning, excluding factories that produced mantas, for a total of 29 factories.
Labor Efficiency: Yarn Produced (Pounds) and Hours of Work
The graphs demonstrate a fairly wide distribution, and little correlation between the amount of hours worked per week and the weekly yarn production. This suggests that labor conditions and factory efficiency varied quite widely in Mexico. While some factories were extremely efficient, others were not. Some owners pushed workers to produce a lot of yarn in a small amount of time, while others workers under conditions more favorable. In this way, the data expresses a diversity of experience in workers’ lives within the Mexican textile industry. Some narratives of the Mexico textile industry would suggest that the industry never rivaled the United States and Britain in terms of its capabilities. Yet clearly, very efficient factories could be established that produced at high rates of production under the right circumstances. This efficiency challenges narratives of textile imperialism, that only technology and skills emerging from the United States or Britain could produce such efficient production. While the data also suggests that exploitation in the factory could be common in places where workers spun a lot of cotton per hour worked, it also demonstrates how workers could labor under more decent conditions. Nothing about the economy or environment of Mexico made labor exploitation or easy work necessarily inherent to factory labor. The data suggests a much more complicated understanding of how labor conditions occurred in Mexico. This next graph now examines the amount of hours work and yarn produced by state.
Average Hours Worked and Yarn Produced (Pounds) Per State
The amount of hours worked per region does not seem to vary widely, only from 12 to 16 hours. This suggests that region did not matter as much for how much workers were expected to labor, and other factors such as the identity of workers may be need to examined to reveal more about labor conditions. Much more variety in occurs in terms of yarn produced, with the factories in Jalisco spinning a large amount more of yarn. This suggests that production may have varied more by region, and elucidates a further topic for research in addition to looking at how race and gender may have impacted the lives of factory workers. Indeed, discrepancies between the number of hours worked in a state such as Veracruz and the yarn produced suggests vastly different efficiencies and technologies at use, and speaks to the diversity of the labor conditions, management theories, and worker activism within factories.
Earnings and Labor Efficiency in 1850-1854
In contrast to the 1843 data, the 1850-1854 data has much more specific information on workers. This allows scholars to understand labor conditions for working people more precisely and investigate labor efficiency more directly. Comparing the number of total workers in a factory to their annual wages earned (in Spanish dollars) can reveal the average compensation per worker. This is based on utilizing information from 38 factories that had both wage and worker data from 1850 to 1854. One way to examine this dataset is through a contour plot, which shows the density and concentration of data points.
Contour Plot of Value of Annual Salary (in Spanish dollars) by Number of Employees
The density in the lower left indicates a high concentration of factories that have a lower number of employees and a lower value of salary and wages. This makes sense that less workers earn less total wages. Yet the concentration and shape of data also suggests a high degree of correlation between factories, even those with more employees. Workers overall earned a relatively stable wage across the different factories in the 1850-1854 dataset. A limited variation of wages could have impacted the ability of workers to bargain. Even as workers moved around, homogenous wages suggest workers may have had difficulty finding work that paid more, giving them less incentive to leave for other jobs with better prospects or the ability to bargain at their worksite. Stability for factor owners in their payment of wages could be detrimental to the lives of workers. As owners often worked in the same elite circles, it could also be evidence for collusion. Yet far more research would be needed to indicate if this was true.
In examining labor efficiency, comparing the number of spindles active to the number workers illustrates the efficiency at which each worker could produce. This also shows the amount of work an individual would have to handle on a daily basis and how this varied by factory. This data is represented through a scatter plot.
Labor Efficiency: Active Spindles per Number of Workers
There is certainly some concentration and bunching in this data, but in general it is fairly vertically scattered, suggesting only a weak correlation between the number of employees and the total spindles in activity. As with the 1843 data, this suggests a greater diversity in factory efficiency and indicates against narratives that universalize the efficiency of Mexican factories. It suggests widespread difference in working conditions and management techniques within factories.
Taking this one step further, the graph below divides the number of active spindles by worker, and then sorts this by state.
Active Spindles per Number of Workers by State
This graph presents a huge amount of variation, with Querétano having the lowest number of spindles per worker, and Veracruz and Puebla producing the most efficiently, many times more than Querétano. The labor efficiency and the amount of spindles a worker had to handle varied greatly across regions. This indicates (again) a diversity of factory production that can be explained partially by geography, but certainly other factors would need to be examined, such as the agency of workers in setting their own production schedules and the identity of those spinning.