Lyuben Georgiev’s innovative ideas concerning Bulgarian language teaching Radomira Videva. Easy-to-read legal texts as a means of INCREASING the cognitive accessibility of legal language

The present paper is focused on Lyuben Georgiev’s innovative ideas concerning Bulgarian language teaching. The author’s new ideas presented in his work The Mother Tongue in Our Junior High Schools and High Schools (a Language Teaching Endeavour) (1933) have not been the subject of scientific research so far. L. Georgiev’s set of didactic ideas is important evidence for the overcoming of the Herbartian model and the orientation of language teaching towards the formation of communicative competencies. Emphasizing the creative nature of pedagogical interaction, Lyuben Georgiev offers a comprehensive system of ideas – a system that is in line with modern trends in language learning.

Easy-to-read legal texts as a means of FACILITATING the cognitive accessibility of legal language

The aim of this article is to examine the easy-to-read legal texts as a means of facilitating the cognitive accessibility of legal language. We begin our study by presenting the characteristics that make the legal language difficult to understand for its addressees non-jurists. Later, the applicability of easy-to-read version to different types of legal texts is considered. Finally, the author proposes a set of practical guidelines on the application of this method in the field of use of the legal language, which are illustrated with examples of foreign experience in thе area.

Domestication of Mathematical Pathologies

Certain mathematical objects bear the name “pathological” (or “paradoxical”). They either occur as unexpected and (temporarily) unwilling in mathematical research practice, or are constructed deliberately, for instance in order to delimit the scope of application of a theorem. I discuss examples of mathematical pathologies and the circumstances of their emergence. I focus my attention on the creative role of pathologies in the development of mathematics. Finally, I propose a few reflections concerning the degree of cognitive accessibility of mathematical objects. I believe that the problems discussed in the paper may attract the attention of philosophers interested in concept formation and the development of mathematical ideas.

Biased memory retrieval in the service of shared reality with an audience: The role of cognitive accessibility

After communicators have tuned a message about a target person’s behaviors to their audience’s attitude, their recall of the target’s behaviors is often evaluatively consistent with their audience’s attitude. This audience-tuning effect on recall has been explained as resulting from the communicators’ creation of a shared reality with the audience, which helps communicators to achieve epistemic needs for confident judgments and knowledge. Drawing on the ROAR (Relevance Of A Representation) model, we argue that shared reality increases the cognitive accessibility of information consistent (vs. inconsistent) with the audience’s attitude, due to enhanced truth relevance of this information. We tested this prediction with a novel reaction-time task in three experiments employing the saying-is-believing paradigm. Faster reactions to audience-consistent (vs. audience-inconsistent) information were found for trait information but not for behavioral information. Thus, audience-congruent accessibility bias emerged at the level at which impressions and judgments of other persons are typically organized. Consistent with a shared-reality account, the audience-consistent accessibility bias was correlated with perceived shared reality about the target person and with epistemic trust in the audience. Among possible explanations, the findings are best reconciled with the view that the creation of shared reality with an audience triggers basic and "automatic" (spontaneous, low-level) cognitive mechanisms that facilitate the retrieval of audience-congruent (vs. audience-incongruent) trait information about a target person.

COVID-19 related anxieties do not decrease support for liberal democracy

Studies carried out at the onset of the COVID-19 pandemic confirmed that under the impression of fear individuals were more willing to tolerate violations of liberal-democratic norms, and supported discriminatory policies to preserve public safety. But what are the potential consequences of the pandemic on citizens’ attitudes beyond its peak? We conducted an original experiment in which we manipulate individuals’ cognitive accessibility of their fears related to COVID-19 one and a half years after the onset of the pandemic. We fielded the experiment in Hungary and Romania–two cases most likely to see such attitudes amplify under the condition of fear. Our intervention was successful in elevating respondents’ levels of worry, anxiety, and fear when thinking about infectious diseases like COVID-19. However, these emotions did not affect individuals’ levels of rightwing authoritarianism, nationalism, or outgroup hostility, or their preferences for specific discriminatory policies aimed to fight a potential resurgence of COVID-19.

Measuring information accessibility and predicting response-effects: The validity of response-certainties and response-latencies

Respondents’ reports about the frequency of everyday behavior are often found to differ considerably when either low- or high-frequency response scales are used to record the answers. It has been hypothesized that the susceptibility to this type of response effect is determined by the cognitive accessibility of the respective target information in respondents’ memories. The first aim of the present paper is to test this hypothesis using two alternative, individual level indicators of the cognitive accessibility of information. These measures are the subjects’ self-reported response certainty and the time needed to answer the question under consideration. A second issue is how response certainties and response latencies should be transformed prior to data analysis in order to maximize their predictive power for response effects. Accordingly, the ability of untransformed measures to predict scale effects is compared with that of logarithmic, square-root and reciprocally transformed versions. The empirical results show that untransformed response certainties and response latencies are equally valid predictors of whether and to what extent subjects’ answers are affected by the presentation of response options. A square-root transformation is found to have no effect on both measures, whereas a logarithmic transformation slightly improves the validity of response certainties. In contrast, a reciprocal transformation proves to have a substantially positive effect on both measures and improves their ability to predict the reliability of respondents’ survey reports.

Analysis of penitentiary, social and legal operators’ perceptions of prison inmates with intellectual disabilities

Objective: To analyze the different perceptions of professionals about the problem of intellectual disability in the prison setting. Material and method: Exploratory-descriptive type. In-depth interviews with legal, social and prison operators of Centro Penitenciario de Zuera (Zaragoza). Results: The narratives of the interviewed subjects point to the aggravating circumstances that a closed social environment can entail for inmates with intellectual disabilities. Communications in the prison administration are written in a technical language that is not understandable for inmates with intellectual deficits. Discusion: There is a need to give more visibility to the case of inmates with intellectual disabilities. Procedures also need to be applied that favour greater cognitive accessibility for this profile of inmates, along with the promotion of awareness raising and training for professionals to enable them to deal with this issue.

Evaluación de la accesibilidad al contenido digital según los espectadores de Netflix

On-demand audiovisual service platforms, such as Netflix, annually generate a large volume of audiovisual content that must comply with current regulations so that as many viewers as possible can access it. Due to the Covid-19 pandemic, 2020 marked a turning point that modified many aspects of life, including entertainment, recognizing online media as one of the most important factors in coping with adversity. This study analyzes international legislation and the social perception of the accessibility of Netflix content in Spain. A mixed research methodology has been used, integrating qualitative and quantitative approaches. The results reveal the progress made and future lines of work regarding the factors that drive the service to continue improving the experience of users of the Netflix platform. The use of adaptive and personalized designs is highlighted according to user preferences with standardized models, translation of dubbing and subtitling into a greater number of languages, the lack of material translated into sign language, the inclusion of users with disabilities and their organizations in audiovisual creation processes, offering specialized training in user experience and accessibility for specialists in the audiovisual industry, updating of the platform in compliance with the W3C guidelines, as well as specific improvements on cognitive accessibility, the use of standardized pictograms and icons and the adaptation to easy reading, among others. Resumen Las plataformas de servicios audiovisuales bajo demanda, como Netflix, generan anualmente un gran volumen de contenido audiovisual que debe cumplir con la normativa vigente para que el mayor número de espectadores posible pueda acceder al mismo. Debido a la pandemia por Covid-19, en 2020 se ha dado un punto de inflexión que modifica muchos aspectos de la vida, incluido el entretenimiento, reconociendo en el medio online uno de los factores más importantes para sobrellevar la adversidad. En este estudio se analiza la legislación internacional y la percepción social de la accesibilidad en el contenido de Netflix. Se ha empleado una metodología de investigación mixta integrando enfoques cualitativos y cuantitativos. Los resultados revelan los avances alcanzados, así como las líneas de trabajo futuras en cuanto a los factores que inciden en el servicio para continuar mejorando la experiencia de los usuarios de Netflix. Se destaca el uso de diseños adaptativos y personalizados según las preferencias de los usuarios con modelos estandarizados, la traducción del doblaje y subtitulado a un mayor número de idiomas, la falta de material traducido a lengua de signos, la inclusión de usuarios y entidades de personas con discapacidad en los procesos de creación audiovisual, la oferta de formación especializada en experiencia de usuario y accesibilidad para los especialistas de la industria audiovisual, la actualización de la plataforma en cumplimiento con las pautas del W3C, así como mejoras específicas sobre la accesibilidad cognitiva, el uso de pictogramas e iconos estandarizados y la adaptación a lectura fácil, entre otros.

Correction: Predicting Health Material Accessibility: Development of Machine Learning Algorithms (Preprint)

BACKGROUND Current health information understandability research uses medical readability formulas to assess the cognitive difficulty of health education resources. This is based on an implicit assumption that medical domain knowledge represented by uncommon words or jargon form the sole barriers to health information access among the public. Our study challenged this by showing that, for readers from non-English speaking backgrounds with higher education attainment, semantic features of English health texts that underpin the knowledge structure of English health texts, rather than medical jargon, can explain the cognitive accessibility of health materials among readers with better understanding of English health terms yet limited exposure to English-based health education environments and traditions. OBJECTIVE Our study explores multidimensional semantic features for developing machine learning algorithms to predict the perceived level of cognitive accessibility of English health materials on health risks and diseases for young adults enrolled in Australian tertiary institutes. We compared algorithms to evaluate the cognitive accessibility of health information for nonnative English speakers with advanced education levels yet limited exposure to English health education environments. METHODS We used 113 semantic features to measure the content complexity and accessibility of original English resources. Using 1000 English health texts collected from Australian and international health organization websites rated by overseas tertiary students, we compared machine learning (decision tree, support vector machine, ensemble classifier, and logistic regression) after hyperparameter optimization (grid search for the best hyperparameter combination of minimal classification errors). We applied 5-fold cross-validation on the whole data set for the model training and testing; and calculated the area under the operating characteristic curve (AUC), sensitivity, specificity, and accuracy as the measurement of the model performance. RESULTS We developed and compared 4 machine learning algorithms using multidimensional semantic features as predictors. The results showed that ensemble classifier (LogitBoost) outperformed in terms of AUC (0.858), sensitivity (0.787), specificity (0.813), and accuracy (0.802). Support vector machine (AUC 0.848, sensitivity 0.783, specificity 0.791, and accuracy 0.786) and decision tree (AUC 0.754, sensitivity 0.7174, specificity 0.7424, and accuracy 0.732) followed. Ensemble classifier (LogitBoost), support vector machine, and decision tree achieved statistically significant improvement over logistic regression in AUC, sensitivity, specificity, and accuracy. Support vector machine reached statistically significant improvement over decision tree in AUC and accuracy. As the best performing algorithm, ensemble classifier (LogitBoost) reached statistically significant improvement over decision tree in AUC, sensitivity, specificity, and accuracy. CONCLUSIONS Our study shows that cognitive accessibility of English health texts is not limited to word length and sentence length as had been conventionally measured by medical readability formulas. We compared machine learning algorithms based on semantic features to explore the cognitive accessibility of health information for nonnative English speakers. The results showed the new models reached statistically increased AUC, sensitivity, and accuracy to predict health resource accessibility for the target readership. Our study illustrated that semantic features such as cognitive ability–related semantic features, communicative actions and processes, power relationships in health care settings, and lexical familiarity and diversity of health texts are large contributors to the comprehension of health information; for readers such as international students, semantic features of health texts outweigh syntax and domain knowledge.