Suchergebnisse

In this article I discuss how various collective art projects involving artists and curators using the city as an exhibition site have transformed artistic discourse in Iceland. Chantal Mouffe´s conception of public space as a battleground and art practices as agnostic interventions into this space raise questions about the branding and commodification of art and cultural institutions. Mouffe believes that despite the unrestrained commercial control of the urban landscape, artists still have the possibility of intervening in the political and economic status quo. Employing Mouffe´s analyses as a guiding principle, the study confirms that the permanent value of art in public spaces need not be limited to individual artists' form, style or content, but may be capable of mobilizing political, critical and artistic discussions within the urban community.

Explanations of sexual violence are an important topic because they reveal the societal context of violence. Perpetrators of violence commonly reject blame, explaining their actions with survivor behavior or the situation. In this study, 397 Icelandic social media posts from Facebook and Twitter were analyzed for explanations of violence. Societal explanations included general negative attitudes towards women, biological essentialism (that men cannot control their sex drive), the entitlement of men to sex and objectification. Survivor explanations included that the survivor had been drinking alcohol at the time of the violence, and that the survivor was expected to fight back to justify the event being classified as violence. The monster stereotype of perpetrators was salient in the accounts, either as fact, or to specifically challenge that idea. The results reveal powerful societal stereotypes when it comes to sexual violence, which need to be counteracted in the future.

The Icelandic-English parallel corpus MaCoCu-is-en 1.0 was built by crawling the ".is" internet top-level domain in 2021, extending the crawl dynamically to other domains as well. All the crawling process was carried out by the MaCoCu crawler (https://github.com/macocu/MaCoCu-crawler). Websites containing documents in both target languages were identified and processed using the tool Bitextor (https://github.com/bitextor/bitextor). Considerable efforts were devoted into cleaning the extracted text to provide a high-quality parallel corpus. This was achieved by removing boilerplate and near-duplicated paragraphs and documents that are not in one of the targeted languages. Document and segment alignment as implemented in Bitextor were carried out, and BicleanerAI (https://github.com/bitextor/bicleaner-ai) and Bifixer (https://github.com/bitextor/bifixer) were used for fixing, cleaning, and deduplicating the final version of the corpus. While the TXT format consists solely of pairs of source and target segments (one or several sentences), each segment pair in the TMX format is accompanied by the following metadata: - source and target document URL; - quality score as provided by the tool BicleanerAI; - translation direction identification: the source segment in each segment pair was identified by using a probabilistic model; - personal information identification ("biroamer-entities"): segments containing personal information are flagged, so final users of the corpus can decide whether to use these segments; - language variants: the language variant of English (British or American) was identified for every segment pair on document and domain level. Notice and take down: Should you consider that our data contains material that is owned by you and should therefore not be reproduced here, please: (1) Clearly identify yourself, with detailed contact data such as an address, telephone number or email address at which you can be contacted. (2) Clearly identify the copyrighted work claimed to be infringed. (3) Clearly identify the material that is claimed to be infringing and information reasonably sufficient in order to allow us to locate the material. (4) Please write to the contact person for this resource whose email is available in the full item record. We will comply with legitimate requests by removing the affected sources from the next release of the corpus. This action has received funding from the European Union's Connecting Europe Facility 2014-2020 - CEF Telecom, under Grant Agreement No. INEA/CEF/ICT/A2020/2278341. This communication reflects only the author's view. The Agency is not responsible for any use that may be made of the information it contains.

The Maltese-English parallel corpus MaCoCu-mt-en 1.0 was built by crawling the ".mt" internet top-level domain in 2021, extending the crawl dynamically to other domains as well. All the crawling process was carried out by the MaCoCu crawler (https://github.com/macocu/MaCoCu-crawler). Websites containing documents in both target languages were identified and processed using the tool Bitextor (https://github.com/bitextor/bitextor). Considerable efforts were devoted into cleaning the extracted text to provide a high-quality parallel corpus. This was achieved by removing boilerplate and near-duplicated paragraphs and documents that are not in one of the targeted languages. Document and segment alignment as implemented in Bitextor were carried out, and BicleanerAI (https://github.com/bitextor/bicleaner-ai) and Bifixer (https://github.com/bitextor/bifixer) were used for fixing, cleaning, and deduplicating the final version of the corpus. While the TXT format consists solely of pairs of source and target segments (one or several sentences), each segment pair in the TMX format is accompanied by the following metadata: - source and target document URL; - quality score as provided by the tool BicleanerAI; - translation direction identification: the source segment in each segment pair was identified by using a probabilistic model; - personal information identification ("biroamer-entities"): segments containing personal information are flagged, so final users of the corpus can decide whether to use these segments; - language variants: the language variant of English (British or American) was identified for every segment pair on document and domain level. Notice and take down: Should you consider that our data contains material that is owned by you and should therefore not be reproduced here, please: (1) Clearly identify yourself, with detailed contact data such as an address, telephone number or email address at which you can be contacted. (2) Clearly identify the copyrighted work claimed to be infringed. (3) Clearly identify the material that is claimed to be infringing and information reasonably sufficient in order to allow us to locate the material. (4) Please write to the contact person for this resource whose email is available in the full item record. We will comply with legitimate requests by removing the affected sources from the next release of the corpus. This action has received funding from the European Union's Connecting Europe Facility 2014-2020 - CEF Telecom, under Grant Agreement No. INEA/CEF/ICT/A2020/2278341. This communication reflects only the author's view. The Agency is not responsible for any use that may be made of the information it contains.