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Complex characters of many kinds? : Gendered representation of inner states in reading anthologies for Czech primary schools

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Author
Segi Lukavská, JanaORCiD Profile - 0000-0001-7886-3306
Kuzmičová, AnežkaORCiD Profile - 0000-0001-9309-2343WoS Profile - AAD-5938-2019Scopus Profile - 55210765800
Publication date
2022
Published in
L1-Educational Studies in Language and Literature
Volume / Issue
22 (1)
ISBN / ISSN
ISSN: 1567-6617
ISBN / ISSN
eISSN: 1573-1731
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  • Faculty of Arts

This publication has a published version with DOI 10.21248/l1esll.2022.22.1.406

Abstract
L1 literacy instruction in Czechia largely relies on reading anthologies, i.e., textbooks containing short excerpts of literary texts from the 19th to 21st century. Focusing on current Year 3 anthologies (N = 13), wehave developed a simple, scalable and transferable analytical procedure examining what types of characters (male, female, animal, other) are represented in the narratives included (N = 530), what experiencedimensions (cognition, emotions, bodily engagement) these characters are attributed, and on what levelsof complexity. We found that female characters overall are strongly underrepresented in the anthologies,including excerpts from the most recent children's literature which is predominantly authored by women.Further, female characters show lower complexity than male characters in emotions, bodily engagement,and especially cognition. In a concluding case study of one particular text, we demonstrate how evenexcerpts with relatively complex characters of both genders may tend to perpetuate deeper imbalances.Our approach provides an experientially nuanced alternative to traditional content analysis yet its morebasic steps remain easy to use for practitioners in selecting literary texts for teaching. It can be applied inresearch anywhere but also in designing classroom activities exploring diversity in stories, whether thefocus is gender, ethnicity, or other.
Keywords
textbooks, Czech literacy curriculum, literary education, gender, emotion, cognition, text analysis
Permanent link
https://hdl.handle.net/20.500.14178/3044
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Full text of this result is licensed under: Creative Commons Uveďte původ 4.0 International

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