FCJ-128 A Programmable Platform? Drupal, Modularity, and the Future of the Web
Bibliographic record
Abstract
Sent as a walking advertisement of Canada’s technology sector, I arrived in Argentina to help a women’s rights organization develop a new website. I began using the Drupal content management platform to construct the site. Its interface brought me into the rarified world of web programming. My experience provides a way of entry into the Drupal platform – a platform I believe is re-programmable. The paper introduces the concept of re-programmability as a processes by which users and code interact to alter software’s running code, and works out this concept through the case of Drupal and how its modular code can be re-programmed by its users. The paper utilizes the theory of transduction to flip the critique of web2.0 platforms on its head – focusing on the processes of becoming a platform, rather than the platform as a final state. This offers a new line of critique for web2.0 platforms, namely how they enact their re-programming.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".