Bibliographic record
Abstract
Abstract: This paper presents the results from a qualitative study that analyzed online comments as an instance of public opinion related to proposed government amendments to the regulations of the Oath of Citizenship. Over six hundred comments submitted to the Canada Gazette web site from February to March 2023 were examined with a text analysis software to identify if the online comments were reflective of specific experiences of the individuals submitting their opinions, or if they were more general and connected to broader political themes. The analysis also looked to uncover any proposals across groups with distinct positions about the regulations that could build a consensus about this public policy related to the Oath of Citizenship process. Résumé: Cet article présente les résultats d’une étude qualitative qui a analysé les commentaires en ligne comme un exemple de l’opinion publique liée aux modifications proposées par le gouvernement aux règlements du serment de citoyenneté. Plus de 600 commentaires soumis sur le site Web de la Gazette du Canada de février à mars 2023 ont été examinés à l’aide d’un logiciel d’analyse de texte afin d’identifier si les commentaires en ligne reflétaient les expériences spécifiques des personnes soumettant leurs opinions, ou s’ils étaient plus généraux et liés à des thèmes politiques plus larges. L’analyse cherche également à découvrir toute proposition de groupes ayant des positions distinctes sur la réglementation qui pourrait construire un consensus sur cette politique publique liée au processus de serment de citoyenneté.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".