IDEAS home Printed from https://ideas.repec.org/a/eee/injoed/v109y2024ics0738059324001032.html
   My bibliography  Save this article

On and off line hate speech and academic performance in secondary education in Cameroon

Author

Listed:
  • Nguemkap Kouamo, Romuald

Abstract

Despite the increasing scientific attention given to hate speech, there is a lack of empirical studies examining the effect of hate speech among secondary school students and its association with academic achievement. The objective of this research is to assess the associations between online and offline hate speech based on gender, religion, ethnic affiliation, and academic achievement. The results suggest that hate speech is not spread evenly across the distribution of students, but rather is concentrated primarily among students with lower academic performance, both online and offline. More specifically, hate speech based on gender and ethnicity was found to have significant and negative associations with educational outcomes when it occurred online. In contrast, hate speech based on religion also had a significant and negative associations with educational outcomes when it occurred offline. It is worth noting that a student's ability to connect to the internet from his or her own phone is positively associated with better school results, while presence on social networks is negatively associated with these results. These results may be helpful considering policies to improve healthy school environments in the future.

Suggested Citation

  • Nguemkap Kouamo, Romuald, 2024. "On and off line hate speech and academic performance in secondary education in Cameroon," International Journal of Educational Development, Elsevier, vol. 109(C).
    • Handle: RePEc:eee:injoed:v:109:y:2024:i:c:s0738059324001032
    DOI: 10.1016/j.ijedudev.2024.103081
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0738059324001032
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijedudev.2024.103081?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Comi, Simona & Origo, Federica & Pagani, Laura & Tonello, Marco, 2021. "Last and furious: Relative position and school violence," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 736-756.
    2. Jung, Juan & Katz, Raúl, 2023. "Exploring the heterogeneous link between broadband investment and coverage expansion using unconditional quantile regressions," Telecommunications Policy, Elsevier, vol. 47(9).
    3. Stijn Baert & Sunčica Vujić & Simon Amez & Matteo Claeskens & Thomas Daman & Arno Maeckelberghe & Eddy Omey & Lieven De Marez, 2020. "Smartphone Use and Academic Performance: Correlation or Causal Relationship?," Kyklos, Wiley Blackwell, vol. 73(1), pages 22-46, February.
    4. Sergio Firpo & Nicole M. Fortin & Thomas Lemieux, 2009. "Unconditional Quantile Regressions," Econometrica, Econometric Society, vol. 77(3), pages 953-973, May.
    5. Shafiq, Muhammad & Parveen, Khalida, 2023. "Social media usage: Analyzing its effect on academic performance and engagement of higher education students," International Journal of Educational Development, Elsevier, vol. 98(C).
    6. Escuadra, Catherine Joy & Magallanes, Krizia & Lee, Sunbok & Chung, Jae Young, 2023. "Systematic analysis on school violence and bullying using data mining," Children and Youth Services Review, Elsevier, vol. 150(C).
    7. Nigel Harriman & Neil Shortland & Max Su & Tyler Cote & Marcia A. Testa & Elena Savoia, 2020. "Youth Exposure to Hate in the Online Space: An Exploratory Analysis," IJERPH, MDPI, vol. 17(22), pages 1-14, November.
    8. Sharma, Abhijit & Woodward, Richard & Grillini, Stefano, 2020. "Unconditional quantile regression analysis of UK inbound tourist expenditures," Economics Letters, Elsevier, vol. 186(C).
    9. Jung, Juan & Katz, Raúl, 2023. "Exploring the heterogeneous link between broadband investment and coverage expansion using Unconditional Quantile Regressions," 32nd European Regional ITS Conference, Madrid 2023: Realising the digital decade in the European Union – Easier said than done? 277982, International Telecommunications Society (ITS).
    10. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    11. Abraham Tamukum Tangwe, 2023. "Peace Education in the Absence of Violence as a Foundation of Learning: The Case of Cameroon," International Journal of Contemporary Education, Redfame publishing, vol. 6(1), pages 15-28, April.
    12. Paek, Seung Yeop & Choi, Yeon-Jun & Lee, Julak, 2023. "Exposure to harmful content and cyberbullying perpetration among South Korean adolescents during COVID-19: The moderating role of parental support," Children and Youth Services Review, Elsevier, vol. 155(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Korom, Philipp, 2016. "Inherited advantage: The importance of inheritance for private wealth accumulation in Europe," MPIfG Discussion Paper 16/11, Max Planck Institute for the Study of Societies.
    2. Huong Thu Le & Ha Trong Nguyen, 2018. "The evolution of the gender test score gap through seventh grade: new insights from Australia using unconditional quantile regression and decomposition," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 7(1), pages 1-42, December.
    3. Victor Chernozhukov & Iván Fernández‐Val & Blaise Melly, 2013. "Inference on Counterfactual Distributions," Econometrica, Econometric Society, vol. 81(6), pages 2205-2268, November.
    4. Vincenzo Carrieri & Francesco Principe & Michele Raitano, 2018. "What makes you ‘super-rich’? New evidence from an analysis of football players’ wages," Oxford Economic Papers, Oxford University Press, vol. 70(4), pages 950-973.
    5. Jean-Marc Fournier & Isabell Koske, 2012. "The determinants of earnings inequality: evidence from quantile regressions," OECD Journal: Economic Studies, OECD Publishing, vol. 2012(1), pages 7-36.
    6. Ramos, Raul & Sanromá, Esteban & Simón, Hipólito, 2022. "Collective bargaining levels, employment and wage inequality in Spain," Journal of Policy Modeling, Elsevier, vol. 44(2), pages 375-395.
    7. Wang, Wen & Lien, Donald, 2018. "Union membership, union coverage and wage dispersion of rural migrants: Evidence from Suzhou industrial sector," China Economic Review, Elsevier, vol. 49(C), pages 96-113.
    8. Akwasi Ampofo, 2021. "Oil at work: natural resource effects on household well-being in Ghana," Empirical Economics, Springer, vol. 60(2), pages 1013-1058, February.
    9. Collischon Matthias, 2019. "Is There a Glass Ceiling over Germany?," German Economic Review, De Gruyter, vol. 20(4), pages 329-359, December.
    10. Sonja C. Kassenboehmer & Mathias G. Sinning, 2014. "Distributional Changes in the Gender Wage Gap," ILR Review, Cornell University, ILR School, vol. 67(2), pages 335-361, April.
    11. Deshpande, Ashwini & Goel, Deepti & Khanna, Shantanu, 2018. "Bad Karma or Discrimination? Male–Female Wage Gaps Among Salaried Workers in India," World Development, Elsevier, vol. 102(C), pages 331-344.
    12. Möller Joachim & Umkehrer Matthias, 2015. "Are there Long-Term Earnings Scars from Youth Unemployment in Germany?," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 235(4-5), pages 474-498, August.
    13. Domenico Depalo & Raffaela Giordano & Evangelia Papapetrou, 2015. "Public–private wage differentials in euro-area countries: evidence from quantile decomposition analysis," Empirical Economics, Springer, vol. 49(3), pages 985-1015, November.
    14. Daniel D. Schnitzlein, 2016. "A New Look at Intergenerational Mobility in Germany Compared to the U.S," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 62(4), pages 650-667, December.
    15. Balestra, Simone & Backes-Gellner, Uschi, 2017. "Heterogeneous returns to education over the wage distribution: Who profits the most?," Labour Economics, Elsevier, vol. 44(C), pages 89-105.
    16. Bos, Iwan & Davies, Stephen & Harrington, Joseph E. & Ormosi, Peter L., 2018. "Does enforcement deter cartels? A tale of two tails," International Journal of Industrial Organization, Elsevier, vol. 59(C), pages 372-405.
    17. Graham, Bryan S. & Hahn, Jinyong & Poirier, Alexandre & Powell, James L., 2018. "A quantile correlated random coefficients panel data model," Journal of Econometrics, Elsevier, vol. 206(2), pages 305-335.
    18. Valentine Fays & Benoît Mahy & François Rycx, 2023. "Wage differences according to workers' origin: The role of working more upstream in GVCs," LABOUR, CEIS, vol. 37(2), pages 319-342, June.
    19. Gregory, Terry & Zierahn, Ulrich, 2022. "When the minimum wage really bites hard: The negative spillover effect on high-skilled workers," Journal of Public Economics, Elsevier, vol. 206(C).
    20. Vu, Tien Manh & Yamada, Hiroyuki, 2020. "Convergence of public and private enterprise wages in a transition economy: Evidence from a distributional decomposition in Vietnam, 2002–2014," Economic Systems, Elsevier, vol. 44(1).

    More about this item

    Keywords

    Hate speech; school results; unconditional quantile regression; Cameroon;
    All these keywords.

    JEL classification:

    • D74 - Microeconomics - - Analysis of Collective Decision-Making - - - Conflict; Conflict Resolution; Alliances; Revolutions
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • O55 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Africa

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:injoed:v:109:y:2024:i:c:s0738059324001032. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/international-journal-of-educational-development .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.