Rupi Kaur, La Poésie 2.0 : numérisation, performance et féminisme transnational
Bibliographic record
Abstract
This research paper focuses on Indo-Canadian poet Rupi Kaur and her work. By analysing Kaur’s work, this dissertation aims to examine the evolution of poetry as it has been influenced by the digital space in today’s society. Literature and poetry have always been shaped by their environment and Instagram poetry is no different. The manner in which Kaur’s poetry has developed on social media like Instagram is a question that prompts several areas of inquiry. The relationship between Instapoetry and different aspects of Kaur’s work brings to light matters of poetic form. To do so, this paper concentrates on different aspects of Kaur’s work by taking into account her poetry in print form, digital activism, oral performances and her political and social engagement as a Canadian woman of color.The first part of this dissertation concerns the evolution that has occurred from the distribution to the reception of digital poetry. Indeed, digital poetry has to cope with new challenges brought by digitization. As the creation, distribution and reception of art are simplified thanks to social networks, anyone with Internet access can create poetry and publish it on digital platforms. In doing so, one positive outcome is that art is no longer limited to a supposed literary elite, as it might have been in the past with poetry in print. However, what is more problematic is the amateurism that it appears to generate. For some critics and scholars, the vulgarisation of poetry on the digital space can be seen as a threat to literary tradition. Indeed, digital poetry is questioning the very definition of art. This article illustrates how digital poetry breaks the rules previously established by academics and refuses to the canonical rules of poetry. Nonetheless, it is important to mention that this refusal of supposed literary rules is not unique to digital poetry because many other traditions and literary movements before the 21st century and even before the 20 th century refused them...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.018 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".