Bibliographic record
Abstract
The right of a citizen to petition Parliament is arguably one of the fundamental ways individuals can engage in democratic processes, by providing their views on what governments should do and requesting action on a particular issue. In 2000, the Scottish Parliament agreed to a trial of an e-petitioner system whereby members of the Scottish public are able to lodge, sign and view petitions to the Scottish Parliament’s Petitions Committee using the internet. Originally developed and hosted by the International Teledemocracy Centre, constituents can now place petitions on the Scottish Parliament Web site in a format that offers a discussion forum for each petition. In 2002, the Queensland government (Australia) launched an e-democracy policy framework that introduced three digital democracy initiatives, including e-petitions. This particular initiative is presented in the case study below. A second Australian state (Tasmania) commenced a 12-month trial based on the Queensland model in July 2004. These three parliaments are the only parliaments to allow e-petitions as at October 2004, although the Canadian, Basque, European parliaments and the German Bundestag have apparently shown an interest in Scotland’s e-petitioner system (MacIntosh, 2004). Although these are only three parliaments that accept electronic petitions, online petitioning is also being used for engaging with governments and elected members. For example, in the United Kingdom, the prime minister’s office accepts electronic petitions and lists those with more than 300 genuine signatures on the number 10 Downing street Web page, together with a link to the government’s response to the petition. However, petitions are not hosted on that site and a separate Web site must be established to explain the purpose of the petition and to collect signatures. Fourteen petitions on a range of diverse issues were listed on the site for the period between April 2001 and July 2003, ranging from 306 to 83,440 signatures per petitioned issue. There are also non-government Web sites providing information about, and tools for, creating online petitions. For example, www.petitiononline.com (Artifice, Inc, 2004) provides a privately sponsored free online hosting service for public petitions that includes an automatic formatting system for the Web petition; collects, displays and maintains petition signatures; automatically rejects duplicate signatures and confirms receipt to signatories; and allows for electronic delivery through e-mailing the petition URL to the target recipient. In mid 2004, the site claims over 20 million signatures have been collected on a range of topics.Request access from your librarian to read this chapter's full text.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.135 | 0.010 |
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".