The prospects of Wattpad: Virtual library of the future or a publisher’s submission site?
Bibliographic record
Abstract
The popularization of the internet has enabled the creation of a number of online publishing outlets. Peer-to-peer platforms allow readers and writers to interact with each other, seemingly eliminating the need for traditional gatekeepers in the form of the editor and publisher. These platforms, however, have been credited with the disturbance of the publishing ecosystem. One popular peer-to-peer site is Wattpad. Conversely, as discussed in this paper, the creators of Wattpad do not want to disrupt the traditional publishing infrastructure but become a part of it. The study analyzes the values incorporated in the design of Wattpad’s website and the mobile app through utilizing the walk-through method of data collection. The researcher outlines how a writer-user and reader-user could potentially be prompted to utilize the platform by analyzing the vision, operating model, and governance of the platform. The study discusses that there are hierarchies at play with the writer-user valued to a greater extent as an individual than the reader-user who is seen by the company as a currency that can be bought and sold. The paper concludes that Wattpad does not want to disrupt the publishing ecosystem because the values incorporated in the design of the platform are similar to the values of traditional publishers. Keywords: publishing industry, self-publishing, online publishing, Wattpad, peer-to-peer platforms, values in design, online users
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.024 | 0.019 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.005 |
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".