Reducing constitutional hyper-rigidity by means of digital technologies: a case study on e-consultations in Canada
Bibliographic record
Abstract
This thesis considers the possibility of using e-consultations as a digital mechanism for democratic participation as part of a reformative proposal to reduce constitutional hyper-rigidity. Hyper-rigidity arises when the procedure for formal amendment within a constitution is so demanding that the constitution is extremely difficult or even impossible to amend. Historically, the protection and maintenance of constitutional stability has often been cited as the reason why such stringent amendment requirements have been necessary. Scholars and politicians often assume that the only way to deal with hyper-rigidity is by means of judicial interpretation. However, in an age in which the use of digital technologies for strengthening democracy has become increasingly prevalent, this thesis examines the suitability for e-consultations to be adjusted to a constitutional level to contribute to a proposal for reducing structural constitutional hyper-rigidity.After examining the case study of e-consultations in Canada, this thesis suggests a new two-part reformative proposal; namely, a reduction in the onerous requirements for formal constitutional amendments that make a constitution hyper-rigid, accompanied by the inclusion of an e-consultation process. Reducing the structural elements of a constitutional amendment mechanism alone could negatively impact constitutional stability. Introducing an e-consultation process alone would only serve to increase the already stringent requirements for formal amendments that make a constitution hyper-rigid. By doing both, structural hyper-rigidity would be reduced whilst constitutional stability would be preserved.To ground this claim, Part I explores constitutional hyper-rigidity as a problem that subverts the popular sovereignty and participation, and the separation of powers principles of democratic constitutionalism. Part II explores whether digital technologies, in theory, can achieve the goals of deliberative democracy and are therefore consistent with democratic constitutionalism. Arising out of this theoretical backdrop, Part III undertakes a case study on Canada’s non-constitutional e-consultations to assess whether this is also true in practice. Part IV explores the possibility of adjusting e-consultations to a constitutional level, as a mechanism through which constitutional amendment rules can be more compliant with democratic constitutionalism, and outlines a reformative proposal.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.034 | 0.009 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".