But Have You Really Heard? Evaluating Respondent Contributions in Government Consultations and the Effects of Missing Details
Notice bibliographique
Résumé
The Government of Canada has demonstrated that it is making an effort to be more open and consultative with its citizens through its membership with the Open Government Partnership.Although adaptations to evolving technologies have provided more opportunities for engagement, it is still questionable as to whether respondent voices are truly being heard.Through a case study on the consultations held for the drafting of the second National Action Plan on Open Government in Canada, this notion of respondent representation was explored.It appeared from the outset that there was overlap between respondent contributions and policy, but a more thorough analysis of the data demonstrated that the details of the respondent contributions were left out.As open government is still new, it can be concluded that positive and gradual progress has been made but there is still room for improvement should the Government of Canada intend to expand its participatory opportunities. But have you really heard? Evaluating respondent contributions in Government consultations and the effects of missing details 1 Chapter: Introduction"What We Heard" is a catch phrase that depicts an accumulation of contributions gathered through a series of public consultations.This catch phrase has been used more and more prominently in numerous contexts, but most importantly for this purpose, it refers to government and public interaction."What We Heard" is meant to show that governments are listening to respondents and reflecting their suggestions in change and ultimately through policy, thus creating a closer citizen-government connection.Through modern technological advancesspecifically the internet -more opportunities for participation have arisen, whereby citizens have the opportunity to participate both online and offline.This enables those who are unable to attend offline consultations to still have their voice expressed in an alternative fashion.The internet has revolutionized communication between citizens and governments, allowing multiple opportunities for interaction.Examples can be seen through sharing information on webpages, the use of email as an interactive tool, social media interactions and web page commentaries (Roy, 2006).These practices have made communication easier, faster and the act of retrieving information more accessible.Not only have governments adopted methods of online participation, such as the collection of respondents' input, but they also use the internet to broadcast calls for participation in offline consultations that expand their reach into the citizen population.Historically, traditional modes of consultation, like physical meetings, were used to gather input on various government activities from a group of citizens who were able to participate in person.However, the combination of both online and offline practices for government communication provides
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,140 | 0,473 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,005 | 0,005 |
| Communication savante | 0,008 | 0,006 |
| Science ouverte | 0,002 | 0,010 |
| Intégrité de la recherche | 0,003 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».