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Gender Bias in Medieval Inquisitions and its Place in Shaping Knowledge about the Heterodox

Published online by Cambridge University Press:  26 August 2025

Davor Salihović*
Affiliation:
Department of History, University of Antwerp, Antwerp, Belgium
José Luis Estévez
Affiliation:
Department of Economic and Social History, University of Helsinki, Helsinki, Finland
*
Corresponding author: Davor Salihović; Email: davor.salihovic@uantwerpen.be; davor.salihovic@gmail.com
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Abstract

This study examines gender bias in the investigative work of medieval inquisitors, focusing on Albert of Castellario’s trial of the Waldensians in Giaveno, Italy, in 1335. Drawing upon advancements in sociological and criminological literature, we conceptualize an inquisitorial trial as a discretionary information-gathering endeavor contingent upon the inquisitor’s judgment in deciding which leads to pursue. Employing social network analysis and survival methods, we evaluate whether Albert demonstrated gender biases in his investigative decisions, particularly regarding the weight assigned to testimonies from men versus women. Our findings demonstrate that Albert was more inclined to investigate men and prioritize their testimonies, even where similar levels of incriminating evidence were present for both genders. These results highlight the influence of societal attitudes toward gender on inquisitorial practices, on the representativeness of historical records, and on prevailing understandings of heretical groups. Furthermore, this study underscores the broader utility of our methodological framework for addressing related historical inquiries, including the political motivations behind the medieval inquisition.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of Social Science History Association
Figure 0

Figure 1. Number of individuals summoned and interviewed, categorized by gender and the date of their appearance.

Figure 1

Figure 2. Network visualization of the accusations reported to the inquisitor. The graph consists of 267 nodes, representing individuals, and 747 ties, representing accusations. Each tie points from the accuser to the accused. Isolated nodes represent testifiers who neither reported anyone nor were accused by others.

Figure 2

Figure 3. Panel A illustrates the balance across key variables (date of testimony, summoned status, and tortured status) when comparing all 34 women to the full group of 76 men (represented by empty white dots), and when comparing the 34 women to only the 48 matched men (represented by filled black dots). Values closer to zero indicate a better balance. Panels B, C, and D display the distribution of both genders across each dimension before matching (unadjusted sample) and after matching (adjusted sample).

Figure 3

Figure 4. Panels A and B show the survival probabilities of men and women reported to the inquisitor, with Panel A using the actual dates of the reports and Panel B using the number of days elapsed since the person was first accused. Panels C and D display the hazards by day, with dented lines representing the observed values and B-spline–smoothed curves illustrating the overall temporal trend. Panels E and F depict the risk sets of callable suspects available to the inquisitor – that is, the number of individuals reported but not yet called to provide their deposition – broken down by gender.

Figure 4

Figure 5. Panel A shows the distribution of accusations made, categorized by the gender of the testifiers. Panels B and C illustrate the distribution of individual homophily levels in the accusations, also differentiated by the testifiers’ gender. Note that homophily levels could not be calculated for individuals who did not report anyone (11 men and 7 women), which explains the difference in sample sizes between Panel A and Panels B and C.

Figure 5

Figure 6. Panel A illustrates the number of individuals reachable by each testifier, comparing scenarios where the accusations reported by the 34 women are excluded (dark gray) against those where accusations from a sample of 34 men out of the 76 interviewed are excluded (light gray). Panel B repeats the same comparison, but in this case, the distribution shows the number of reachable individuals when sampling only from the 48 men who match women in terms of deposition date, summoned status, and tortured status.

Figure 6

Table 1. Descriptive statistics for the variables in the analyses. Data presented in person-day format (N = 3,497)

Figure 7

Figure 7. Pairwise Pearson correlation coefficient among the variables used in the analyses. Coefficients with p values greater than 0.05 are crossed out.

Figure 8

Table 2. Tests of proportionality of hazards. Highlighted statistics indicate problematic covariates, with the p value close to or under 0.05

Figure 9

Table 3. Cox proportional hazards models. For easier interpretation, the estimates show coefficients rather than hazard ratios (i.e., ${e^\beta }$)

Figure 10

Figure 8. Smoothed Schoenfeld residual plots from Model 1 for the covariates “Gender (woman)” and “Day of accusation,” plotted against analysis time and log-transformed analysis time. The time-varying patterns suggest that the effects of both covariates change over time, with the effect of gender tending to zero as time progresses.

Figure 11

Table 4. Log-normal accelerated failure time models for the time to summons

Figure 12

Figure 9. Log-normal hazard and survival functions for women and men as estimated in Model 8. Note the shift of the hazard function for women toward later times, corresponding to the higher $\mu $ parameter for women.