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Enregistrement W7083892935

10 Misogynistic+ Hate+ Speech+against+ Female+ Politicians+on+ New+ Media+in+ Pakistan

2025· other· en· W7083892935 sur OpenAlexaboutno aff

Notice bibliographique

RevueInternet Archive (Internet Archive) · 2025
Typeother
Langueen
DomaineMedicine
ThématiquePhysical Activity and Health
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPoliticsDigital mediaPolitical communicationRepresentation (politics)The InternetDigital RevolutionSurvey researchSpace (punctuation)
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Abstract Pakistan has been observed considerable rise in women’s political representation similar to other nations, but along with this growing rate of misogynistic attacks have also been noticed. Under the umbrella of anonymity, social values of society constantly dishonoured, prominent political names Maryam Nawaz, Uzma Bukhari, Shiren Mazari, Hina Rabani Khar, Sherry Rehman, and others have faced hate speech, digital abuse that is irrelevant to their political performances. Such moral policing reflects unease of society to see women in leadership roles and holding authority in their hands. New media platforms have important and central space for political discourse in Pakistan’s changing digital landscape. While on one side digital advancement paving the way for global political communication, on other hand technology has led to increase digital abuse and hate speech particularly targeting women in online space. Digital spaces like YouTube, Twitter/ X, Instagram, tiktok, Facebook, and many other platforms become known as powerful tools of technology, at present all traditional media shifted to digital platforms according to the requirement of time. This study “Misogynistic hate speech against female politicians on new media in Pakistan” examines how online misogyny affects its interconnected aspects including perceived political authenticity, political affiliation, political participation, and public shaming. Four hypotheses were created to check the relationship of misogynistic behaviour with interconnected features. The study is descriptive nature study, quantitative research design used for data collection and survey questionnaire disseminated among 220 female political representatives who served at district, divisional, provincial and national level through convenient sampling technique. This research study aims to analyse and understand the perception of female politicians because these are the one who directly encountered misogyny on new media platforms. This study emphasizes how misogyny structured both public narratives and victim’s attitude through digital spaces. References Anees, M. (2022). Cybercrime law in Pakistan: An ultimate guide . Graana. https://www.graana.com/blog/cybercrime-law-in-pakistan/ Anees, S. M. (2023, May 24). Where are the women in Pakistan's politics? The Diplomat . https://thediplomat.com/2023/05/where-are-the-women-in-pakistans-politics/ Anderson, M. (2016, August 15). The hashtag #BlackLivesMatter emerges: Social activism on Twitter. Pew Research Center . https://www.pewresearch.org/internet/2016/08/15/the-hashtag-blacklivesmatter-emerges-social-activism-on-twitter/ Azeem, M. (2020). Islam, Pakistan and women leadership: A case study of Benazir Bhutto. Journal of Politics and International Studies, 6 (2), 1-20. http://pu.edu.pk/images/journal/politicsAndInternational/PDF/3_v6_2_2020.pdf Barroso, R. L., & Barroso, B. V. L. (2023). Democracy, social media, and freedom of expression: Hate, lies, and the search for the possible truth. Chicago Journal of International Law . https://cjil.uchicago.edu/print-archive/democracy-social-media-and-freedom-expression-hate-lies-and-search-possible-truth Bulut, E., & Yoruk, E. (2017). Digital populism: Trolls and political polarization of Twitter in Turkey. International Journal of Communication, 11 , 4093-4117. https://ijoc.org/index.php/ijoc/article/view/6702/2158 Daniele, G. (2024, January 18). Why are female politicians more often targeted with violence? New findings confirm depressing suspicions. The Conversation . https://theconversation.com/why-are-female-politicians-more-often-targeted-with-violence-new-findings-confirm-depressing-suspicions-238483 Dawn. (2022, January 10). Cybercrime complaints topped 100,000 in 2021: FIA chief. https://www.dawn.com/news/1667248 Dawn. (2024, February 15). Cyber complaints. https://www.dawn.com/news/1755206 European Conference of Presidents of Parliament. (2019). Women in politics and in the public discourse . Council of Europe. https://edoc.coe.int/en/violence-against-women/7989-women-in-politics-and-in-the-public-discourse.html Field, A. (2018). Discovering statistics using IBM SPSS statistics (5th ed.). Sage. George, D., & Mallery, P. (2016). IBM SPSS Statistics 23 step by step: A simple guide and reference (14th ed.). Routledge. Gregory, S. (2019). Cameras everywhere revisited: How digital technologies and social media aid and inhibit human rights documentation and advocacy. Journal of Human Rights Practice, 11 (2), 412-428. https://doi.org/10.1093/jhuman/huz022 Hunt, E., Evershed, N., & Liu, R. (2016, June 27). From Julia Gillard to Hillary Clinton: Online abuse of politicians around the world. The Guardian . https://www.theguardian.com/technology/datablog/ng-interactive/2016/jun/27/from-julia-gillard-to-hillary-clinton-online-abuse-of-politicians-around-the-world Ibrohim, O. M., & Budi, I. (2023). Hate speech and abusive language detection in Indonesian social media: Progress and challenges. Heliyon, 9 (6), e18647. https://doi.org/10.1016/j.heliyon.2023.e18647 Kaneez, F. (2023). Exploring the influence of sociocultural norms and gender biases on women's empowerment in Pakistan . Harvard University. Kendall, E. (2023). Misogyny. In Encyclopedia Britannica . https://www.britannica.com/topic/misogyny Khalid, A. M. (2021). Assessment of gender-role attitudes among people of Pakistan. Open Journal of Social Sciences, 9 , 338-350. https://www.scirp.org/journal/paperinformation?paperid=114000 Khan, R. K. (n.d.). Cyber laws in Pakistan . Pakistan Journalists Association. Kline, P. (2013). Handbook of psychological testing (2nd ed.). Routledge. Kwak, H., Lee, C., Park, H., & Moon, S. (2010). What is Twitter, a social network or a news media? Proceedings of the 19th International Conference on World Wide Web , 591-600. https://snap.stanford.edu/class/cs224w-readings/kwak10twitter.pdf Lee, J. K., & Park, H.-G. (2011). Measures of women's status and gender inequality in Asia: Issues and challenges. Asian Journal of Women's Studies, 17 (1), 7-31. https://doi.org/10.1080/12259276.2011.11666106 Masroor, F., Khan, N. Q., Aib, I., & Ali, Z. (2019). Polarization and ideological weaving in Twitter discourse of politicians. Social Media + Society, 5 (4). https://doi.org/10.1177/2056305119891220 National Commission on the Status of Women. (2023). Digitalisation & women in Pakistan . United Nations Development Programme. https://www.undp.org/sites/g/files/zskgke326/files/2023-07/digitalisation_women_in_pakistan_-_ncsw_report_2023.pdf Prasad, R. (2019, November 28). How Trump talks about women - and does it matter? BBC News . https://www.bbc.com/news/world-us-canada-50563106 Sakki, I. (2023). Emotion, language and communication, race, ethnicity and culture: Contested meanings and uses of hate speech. The Psychologist, 36 , 32-35. https://www.bps.org.uk/psychologist/contested-meanings-and-uses-hate-speech Shehab, R. (1989). History of Pakistan . Sang-e-Meel Publications. Spark, S. L., & Tuysuz, G. (2014, November 25). Rights groups slam Turkey's Erdogan over remarks on women. CNN . https://edition.cnn.com/2014/11/25/world/europe/turkey-erdogan-women/index.html Tribune. (2023, September 10). Cyber crime in Punjab increased manifold in past quinquennial. https://tribune.com.pk/story/2445839/poor-policing-cyber-crime-in-punjab-increased-manifold-in-past-quinquennial United Nations. (2021, March 16). Female government leaders recount personal experiences of threats, attacks, structural obstacles [Press release]. https://press.un.org/en/2021/wom2206.doc.htm United Nations Population Fund. (2022). Women journalists threatened with sexual violence, hate speech . https://www.unfpa.org/news/women-journalists-threatened-sexual-violence-hate-speech United Nations Population Fund. (2023). Five reasons why: Women and girls must have equal rights in our digital world . https://www.unfpa.org/news/five-reasons-why-women-and-girls-must-have-equal-rights-our-digital-world World Economic Forum. (2024). Global gender gap report 2024 . https://www.weforum.org/publications/global-gender-gap-report-2024/ Zarouni, A. E. (2022). Detection of hateful comments on social media [Master's thesis, Rochester Institute of Technology]. RIT Scholar Works. https://repository.rit.edu/theses/11471/

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,032
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0020,000
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0010,001
Intégrité de la recherche0,0000,002
Charge utile insuffisante (le modèle a refusé de juger)0,0200,008

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,027
Tête enseignante GPT0,317
Écart entre enseignants0,290 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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