Towards digital constitutionalism? Mapping attempts to craft an Internet Bill of Rights
Bibliographic record
Abstract
The article develops digital constitutionalism as a common term connecting a constellation of initiatives that seek to articulate a set of political rights, governance norms, and limitations on the exercise of power on the Internet. We start by reporting on insights from an analysis of the substantive content of over 30 such documents, and make reference to the political and technological changes to which they may relate. We offer an overview of the core actors in the area of digital constitutionalism and a brief exploration of the processes by which their initiatives aim to entrench rights into law and practice. We discuss the changing sites of political and legal intervention, including a more recent focus on domestic and regional initiatives. Finally, we consider what a future research agenda could entail.
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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 | 0.018 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.010 | 0.014 |
| Science and technology studies | 0.005 | 0.036 |
| Scholarly communication | 0.019 | 0.028 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 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".