{"id":68964,"date":"2025-07-15T19:35:42","date_gmt":"2025-07-15T19:35:42","guid":{"rendered":"https:\/\/revista-apunts.com\/?p=68964"},"modified":"2025-10-03T16:23:39","modified_gmt":"2025-10-03T16:23:39","slug":"reliability-of-the-image-category-observation-system-in-opponent-sports","status":"publish","type":"post","link":"https:\/\/revista-apunts.com\/en\/reliability-of-the-image-category-observation-system-in-opponent-sports\/","title":{"rendered":"Reliability of the Image Category Observation System in Opponent Sports (SOCIDA)"},"content":{"rendered":"\n

Abstract<\/strong><\/h2>\n\n\n\n

The Image Category Observation System in Opponent Sports (SOCIDA by its Spanish acronym) was developed to analyze body and gender stereotypes present in images from books and specialist manuals related to the group of opponent sports and, more specifically, to combat sports. The influence of stereotyped models in images on individuals\u2019 processes of socialization, perception and belief formation is profound and significant. The main aim of this study was to validate the SOCIDA observation system, which is structured into two dimensions, eight criteria and 15 categories. Validation was carried out using systematic observational methodology, including consensual agreement, expert judge review, observer training and analysis, and the assessment of intra- and interobserver agreement, thereby ensuring the reliability and generalizability of the results. The data were managed through a web application developed in PHP, an open-source server-side scripting language used for dynamic web applications, which facilitates collaboration, enhancement and customization of the tool according to users\u2019 needs. SOCIDA demonstrated high levels of agreement, internal consistency and reliability, with values of \u03b1=.841 and \u03ba\u2265.826 as the mean across its items. It was concluded that this tool is suitable for physical activity teachers and researchers to identify and analyze body and gender stereotypes in images from opponent sports, contributing to a more critical understanding of the models represented in educational materials.<\/p>\n\n\n

Keywords:<\/strong> body stereotypes<\/span>, combat sports<\/span>, gender stereotypes<\/span>, observational methodology<\/span>, teaching materials<\/span><\/p> <\/div> \n\n\n\n

Introduction<\/strong><\/h2>\n\n\n\n

The issue of body and gender representation in sport has been addressed from various disciplinary perspectives, and highlights the need for intersectional approaches that consider multiple axes of inequality (Esposito & Evans-Winters, 2022<\/a>; Vandellos et al., 2023<\/a>). Gender, corporality, biological traits and disability interact in complex ways in the construction of social stereotypes, influencing both the experiences of athletes in these disciplines and the public perception of them. Abioye and Nyawo (2020)<\/a> point out that gender-based structural barriers are deeply rooted in social culture, resulting in normalized forms of exclusion. In this context, intersectionality is essential to analyze how certain identities may be simultaneously rendered invisible or hypervisible, according to Crenshaw (1989)<\/a> and PPape et al. (2023)<\/a>. Vandellos et al. (2023)<\/a> underline the importance of considering the interaction between race, class, gender, sexual orientation and age. As a result, femvertising has emerged as an advertising trend that seeks to empower and challenge traditional stereotypes.<\/p>\n\n\n\n

Combat sports have traditionally been regarded as masculine spaces that reproduce gender stereotypes, reinforcing traditional models of male strength and dominance (Channon & Phipps, 2017<\/a>). When women enter these disciplines, they are confronted by a negative social imaginary that portrays them as violating conventional standards of femininity due to their strength, physique or physical expression (Gentile et al., 2018<\/a>; Hartmann-Tews, 2019<\/a>; Pastor, 2021<\/a>). This issue is compounded by the way in which female athletes are depicted in the media and specialized manuals: less frequently, in static poses, with a focus on appearance, and rarely in competitive action (Juliet, 2024<\/a>). In contrast, male athletes are usually portrayed in athletic performance contexts and occupy more visual space (Delorme & Testard, 2015<\/a>).<\/p>\n\n\n\n

Visual representation in sport is not neutral: it shapes identities, validates roles and contributes to the normalization of gender hierarchies. These images serve as powerful symbolic mechanisms that reflect and shape reality (Mu\u00f1oz-Mu\u00f1oz & Salido-Fern\u00e1ndez, 2022<\/a>). Consequently, the way in which women and men are visually and discursively represented in the sporting arena influences their professional and social recognition, and directly affects their identity (Gentile et al., 2018<\/a>; Hartmann-Tews, 2019<\/a>; Pastor, 2021<\/a>).<\/p>\n\n\n\n

According to Camerino et al. (2020)<\/a>, one of the key factors in reinforcing these social constructs is somatotype. The interaction between body biology and cultural gender ideals shapes how female athletes are perceived and valued. Andersen and Swami (2021)<\/a> stress that these variables have a particular impact on adolescent girls, who are constantly judged based on their bodies. Tinoco et al. (2023)<\/a> demonstrate how stereotypes related to skin color and body weight are common sources of ridicule and discomfort among female athletes, which can even lead them to abandon their sporting careers. This pressure stems not only from the male gaze, but also from the stigma attached to disciplines that are traditionally considered masculine, such as combat sport (Gentile et al., 2018<\/a>; Channon & Matthews, 2018<\/a>). One of the least explored aspects of this perspective is the intersection of gender and disability in sport. Paccaud and Baril (2021)<\/a> point out that this relationship has only recently received attention in sport studies, despite its importance in understanding stigmatization dynamics. In combat sports, this situation is particularly acute, as gender acts as a determining factor in how participation is portrayed and valued (Paccaud, 2022<\/a>; Calow, 2022<\/a>).<\/p>\n\n\n\n

Given this context, there is a need for rigorous analysis of the visual discourses found in teaching and promotional materials related to combat sports. This study addresses the factors that promote stereotypes through systematic observational methodology (Anguera et al., 2020<\/a>), using a validated category system that enables the identification of key dimensions for analyzing visual representation.<\/p>\n\n\n\n

Specifically, the study proposes the validation of the Image Category Observation System in Opponent Sports (SOCIDA by its Spanish acronym) (Ruiz-Sanchis et al., 2025<\/a>). Although the tool has already been published in a specialist manual, its validation is necessary to ensure its reliability and relevance to its specific context of application. SOCIDA was developed based on previous work examining how the body is visually treated in sport (Mu\u00f1oz-Mu\u00f1oz & Salido-Fern\u00e1ndez, 2022<\/a>; Delorme & Testard, 2015<\/a>). It provides a cross-cutting, intersectional reading of images found in sports books and manuals and incorporates variables related to technical, bodily and contextual representation.<\/p>\n\n\n\n

The main aim of this study was thus to validate an observational tool designed to describe gender and body stereotypes in the images included in technical books and manuals on opponent sports. These materials contained technical-tactical, psychological, physical and regulatory content. The methodological approach adopted a critical and intersectional perspective in order to uncover visual patterns that reproduce inequality, invisibility and hierarchies in how bodies and genders are represented in the field of combat sports.<\/p>\n\n\n\n

Methodology<\/strong><\/h2>\n\n\n\n

The study was framed within an instrumental design based on observational methodology (Anguera, 1991<\/a>), which enabled the structured, objective and sequential recording of observable behaviors in natural contexts.<\/p>\n\n\n\n

The ad hoc<\/em> tool, according to the typology proposed by Anguera et al. (2011)<\/a>, was classified as nomothetic, as it focused on the systematic comparison of multiple still images extracted from different sports manuals and books, allowing for the analysis of common patterns and divergences in visual representations. It was also cross-sectional, as it was limited to images captured at specific moments, and multidimensional, since it incorporated several analysis criteria related to technical, aesthetic and sociocultural aspects (Anguera et al., 2020<\/a>).<\/p>\n\n\n\n

A qualitative content analysis with an interpretative approach was used for data processing. According to Neuendorf (2017)<\/a>, this technique enables the identification and interpretation of the implicit meanings in visual material, based on the context in which it was produced, especially in relation to sociocultural values and possible stereotypes represented.<\/p>\n\n\n\n

Sample <\/strong><\/h3>\n\n\n\n

The sample consisted of 240 images (n<\/em> = 240), with 120 representations per observer round. These were distributed equally, with 24 representations for each of the five combat sports analyzed: fencing, boxing, taekwondo, judo, and Olympic wrestling (men\u2019s and women\u2019s freestyle). This set of images represented approximately 2% of the total visual content available in the 36 selected books and specialized manuals. The images were selected through random sampling with structural representativeness criteria, ensuring the inclusion of all identified grouping types. Furthermore, the selected images covered the 15 categories defined according to the eight criteria established in the analysis system.<\/p>\n\n\n\n

The sample consisted of 40 individual representations (33%), 50 paired (42%), 20 group (17%) and 10 mass representations (8%). The selected books and manuals had to meet the following inclusion criteria: 1) Specialized manuals that explicitly, systematically and orderly provide information for the initiation and improvement of performance in the sport modality, as well as instructions considered necessary for the execution of defined activities in the technical-tactical, regulatory, physical preparation and\/or training support processes; 2) Manuals written in Spanish and English. 3) Manuals printed between 2012 and 2022.<\/p>\n\n\n\n

Recording Tool<\/strong><\/h3>\n\n\n\n

The observation tool used in this study was the Image Category Observation System in Opponent Sports (SOCIDA, by its Spanish acronym) (Ruiz-Sanchis et al., 2025<\/a>). Although the tool had already been published, this study focused on its validation to ensure the methodological robustness of the collected data.<\/p>\n\n\n\n

SOCIDA enabled the structured, systematic and multivariate recording of data and images related to the combat sports included in the Olympic programme for the Paris 2024 Games.<\/p>\n\n\n\n

From a technical perspective, the SOCIDA platform was developed as a web application programmed in PHP, allowing online use from any device with internet access. The interface was designed to be simple, intuitive and operationally efficient, minimizing potential errors in the observers\u2019 recording and analysis process. The web application is accessible from the sub-domain http:\/\/freesocida.giepafs.net hosted on a virtual private server (VPS) with Linux operating system (CentOS 6.4). The platform was programmed in PHP (v.8.1) and uses a MySQL relational database (v.5.3.1), which enables the structured insertion, storage and management of observational data. This digital environment allows for continuous data updating, avoids duplication, and automates the storage of records, thereby improving the quality and reliability of the analysis. SOCIDA is structured into two dimensions (general and specific), eight criteria and 15 categories, designed to be exhaustive and mutually exclusive to ensure the reliability of the coding system and to facilitate subsequent multivariate analysis. <\/p>\n\n\n\n

The registration and analysis process in the platform is conducted in two sequential phases: <\/p>\n\n\n\n

First, the typological classification of the image, which considers the visual grouping based on the number of people depicted: individual (one person), paired (two people with clearly visible faces and\/or full bodies), group (between three and 10 people in an organized sports practice setting), and mass (more than 10 people in the image). <\/p>\n\n\n\n

Second, the coding of metadata and observational variables: an identification code is assigned to each image, along with additional variables such as the sport represented, publication year of the manual, image size, and use of color or black and white. These data appear in the user interface alongside the criteria and categories for analysis, thus facilitating the coding and review process by the observers.<\/p>\n\n\n\n

Table 1 summarizes the criteria and categories for the general dimension, applicable to all images. Table 2 describes the criteria and categories for the specific dimension, differentiated by visual grouping type: individual, pair, and group. For pairs, items are duplicated to code the left and right figures, while for groups, items are subdivided by the number of men and women observed in each category. Table 3 presents the reduced set of 12 criteria and categories for the specific dimension applicable to mass groupings (more than 10 people), where coding is done using percentage approximation and binary detection of item presence.<\/p>\n\n\n\n

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Table 1<\/strong><\/p>\n\n\n\n

Overall dimension, criteria, categories and indicators of the SOCIDA tool<\/em><\/p>\n\n\n\n

See Table<\/a><\/p>\n<\/div>\n<\/div>\n<\/div><\/div>\n\n\n\n

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Table 2<\/strong><\/p>\n\n\n\n

Specific dimension: criteria and categories for individual, paired and group formats<\/em><\/p>\n\n\n\n

See Table<\/a><\/p>\n<\/div>\n<\/div>\n\n\n\n

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Table 3<\/strong><\/p>\n\n\n\n

Specific dimension, criteria and categories for mass grouping (>10 people)<\/em><\/p>\n\n\n\n

See Table<\/a><\/p>\n<\/div>\n<\/div>\n<\/div><\/div>\n\n\n\n

Data Quality Control<\/strong><\/h3>\n\n\n\n

To validate SOCIDA, three expert judges were intentionally selected based on their professional and academic backgrounds. Inclusion criteria were: a) experience in the study of body and gender stereotypes in physical activity; b) over five years of experience in intersectional image analysis; c) experience as coaches or teachers familiar with specialized combat sports manuals.<\/p>\n\n\n\n

This panel critically reviewed the tool\u2019s category system. Five basic criteria were used to evaluate the items\u2014sufficiency, clarity, coherence, relevance, and effect\u2014using a 4-point Likert scale. Qualitative and quantitative observations were provided for each unit, enabling adjustment and refinement of deficient items. This process enhanced content validity and ensured the tool\u2019s quality and relevance.<\/p>\n\n\n\n

To ensure the reliability of the coding process, three observers were intentionally selected. Although two observers are sufficient according to Neuendorf (2017)<\/a>, this number was chosen to strengthen the study\u2019s methodological rigor. Selected observers met the following requirements: a) prior experience in intersectional image analysis research; b) work with illustrated images in the sports domain; c) access to the internet to participate online.<\/p>\n\n\n\n

The observers demonstrated a high level of expertise in visual analysis of combat sports. Their experience facilitated coding and contributed qualitative judgements and insights that enhanced the analysis system. <\/p>\n\n\n\n

Training Procedure and Reliability Calculation<\/strong><\/h3>\n\n\n\n

The validation of the category system and agreement analysis involved several strategies. First, dimensions, criteria and categories were constructed based on documentary reviews and consensual agreement (Lapresa et al., 2021<\/a>). Next, a descriptive manual-protocol of the tool was developed. The system was then reviewed by three expert judges. Subsequently, three observers were trained and tested in image analysis. Finally, intraobserver, interobserver and generalizability coefficients were calculated (Sastre et al., 2022<\/a>).<\/p>\n\n\n\n

Observer training consisted of a session where the category system was presented, doubts were clarified, and a subset of images (not included in the final sample) was coded. The aim was to standardize coding criteria and ensure operational understanding of the categories (Sastre et al., 2022<\/a>). To evaluate interobserver reliability, Cohen\u2019s kappa index (Cohen, 1960<\/a>) was calculated for dichotomous and presence\/absence variables, and Krippendorff\u2019s alpha (Krippendorff, 2019<\/a>) was used for nominal categories. Agreement values exceeded .80 across all categories, interpreted as \u201coptimal\u201d or \u201calmost perfect\u201d (Landis & Koch, 1977<\/a>). These results ensured the consistency and reliability of the coding system. For intraobserver agreement, kappa values were calculated for the same observer at two different points in time (Table 4). The initial calculation showed a mean of .820, while the final one yielded .882 (Cohen et al., 2011<\/a>), demonstrating high reliability.<\/p>\n\n\n\n

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Table 4<\/strong><\/p>\n\n\n\n

Intraobserver agreement, first and second round in the specific dimension<\/em><\/p>\n\n\n\n

See Table<\/a><\/p>\n<\/div>\n<\/div>\n<\/div><\/div>\n\n\n\n

To evaluate interobserver agreement, kappa was calculated based on the same situation observed independently by the three evaluators (Table 5). Two weeks later, the procedure was repeated, obtaining a mean kappa of .843, indicating a high level of agreement. As a complementary measure, Cronbach\u2019s alpha was also calculated to assess consistency among observers, resulting in a value of .737 (Losada & Arnau, 2000<\/a>).<\/p>\n\n\n\n

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Table 5<\/strong><\/p>\n\n\n\n

Interobserver agreement, first and second rounds<\/em><\/em><\/em><\/em><\/em><\/em><\/em><\/em><\/em><\/em><\/em><\/p>\n\n\n\n

See Table<\/a><\/p>\n<\/div>\n<\/div>\n<\/div><\/div>\n\n\n\n

SOCIDA was adapted based on the data. When comprehension issues arose, some categories were revised and adjusted. After the modifications, observers reported improved global assessment of content validity and the adequacy of the criteria:<\/p>\n\n\n\n