Rethinking the Politics of Scale: Independent Publishing for Social Changes in Hong Kong and Beyond
Bibliographic record
Abstract
Using insights from interviews with 45 indie practitioners in the book publishing industry, descriptive statistics, and a detailed analysis of indie publications, this thesis investigates why and how Hong Kong citizens employed indie publishing and bookselling to drive social change from 2012 to 2022. This investigation is framed through the perspectives of the politics of medium and the politics of scale. Conventionally, Hong Kong has cultivated a long tradition of publishing activism dating back to the early colonial period of the late 19th century. This aligns with scholarly perceptions of indie publishing as a form of cultural resistance against dominant oppressive structures. This historical legacy has bequeathed abundant tangible and intangible resources to subsequent generations of publishers and booksellers. The dynamics of cultural resistance and domination have been further complicated by digital transformations, which unveil new sites of contestation. The publishing industry, to a certain extent, has benefited from various digital tools, ranging from laser printing to social media and crowdfunding platforms. These tools are advantageous for small-scale practices and have reduced entry barriers for some part-time players. Meanwhile, small-scale operations inherently exhibit several strengths in cultural production, including lower fixed costs that afford higher market autonomy, greater flexibility in creative experimentation and social responses, and closer proximity between publishers, booksellers, and readers, fostering affective solidarity. Therefore, when political crises occur, creating an immense urge for reading, writing, and political engagement, publishing and bookselling serve as alternative venues for former politicians and journalists to participate politically. In this context, Hong Kong witnessed a surge in indie publishing and bookselling activities. However, when the government intensified repression, indie publishing and bookselling encountered limitations, prompting many practitioners to join a significant migration wave from Hong Kong to Britain, Canada, and Taiwan. Nevertheless, for some, small-scale practices embody an additional layer of pragmatism, enabling them to restart their endeavors in their new homes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".