The Self-Publishing Phenomenon and Poetry in the 21st Century: Rupi Kaur
Bibliographic record
Abstract
This dissertation will explore the great impact that technology has had on many aspects of daily life and, more specifically, the influence and importance that it has had over literature in recent years. Firstly, these important technological advances have dovetailed into new ways of writing and reading literature. There has been an ever-increasing development in the way of reading and searching for information, from the traditional method, characterized by concrete traditional printed sources, to the electronic one (i.e. electronic book devices), with which we are already living. Secondly, technology has not only influenced reading habits, but also the way in which these books come to light as a result of a new phenomenon known as ‘self-publishing.’ The analysis of this new phenomenon will reveal the advantages and disadvantages that it poses. This dissertation will also focus on Indian-Canadian poet Rupi Kaur, who decided to resort to the self-publishing phenomenon in order to launch onto the market her first collection of poetry Milk and Honey. It will tackle the importance that social networks have over poetry nowadays, thus building a bridge and a strong link between poetry and social networks. This dissertation will study her peculiar style of writing poetry, mainly as a means to denounce and protest against certain social issues. In order to carry out this analysis, support my arguments and strengthen my conclusions I will rely on a number of articles, books and websites on the influence of Internet on literature, self-publishing and Rupi Kaur in order to analyse this subversive and most influential collection of poetry, and show it as a wonderful illustration of this new cultural phenomenon.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".