PSE policies Canada (July 2024)
Notice bibliographique
Résumé
PSE policies Canada (July 2024) Project Team Ray Huang - [Github] [https://orcid.org/0009-0008-1699-6267] Tim Ribaric - [Github] [https://orcid.org/0000-0001-9229-8569] Rahul Kumar - [Github] [https://orcid.org/0000-0002-4247-6045] Policies play a pivotal role in defining the boundaries of what is permissible and what is not. Among these, academic integrity policies are crucial in outlining acceptable and unacceptable behaviours in academic settings. These policies were available in various formats on institutional websites. This repository contains text versions of academic integrity policies from English-language, publicly supported postsecondary education (PSE) institutions in Canada. We recognize that policies often lag behind innovation (e.g., Barzotto et al., 2019; Marcus, 1981; Rodríguez‐Pose & Wilkie, 2018); consequently, this repository also includes guidelines that are sometimes issued to address the disruption caused by GenAI. We aimed to examine their similarities and differences concerning responsibilities and freedoms outlined in the policies and guidelines. In the research for which these policies were collected, we were particularly interested in investigating how they have evolved (or not) in response to the proliferation of generative artificial intelligence (GenAI). Using a computer script, these policies were collected on July 29, 2024 after their location was populated in the attached CSV file. Examining these policies and guidelines using computerized techniques required tokenization to perform Latent Dirichlet Allocation (LDA) and Term Frequency-Inverse Document Frequency (TFIDF) analyses. These processed files are also included in the repository. Details of the various files and their website locations are provided in the CSV file within the repository, and the README.md contains additional pertinent information. Our preliminary results indicate that the policies are indeed trailing the innovation and disruption brought about by GenAI. For more details, please visit our project website where the published results will also be posted. Document Description & Summary That dataset is comprised of the academic integrity policies of English speaking, publically funding, Canadian institutions current to July 29, 2024. Harvested information is categorized into the following: policies - documents that are binding</> guidelines - documents that are not binding but represent best practices, guidelines, etc. followed up policies - documents that are secondary responses Description of files PSE_Policies_Collection.csv A listing of all of the Canadian colleges and universities with a posted Academic Integrity policy investigated in this study. Columns in data: Name of the PSE U15 or not College/University Province URL of the PSE URL2 (filled if instiution has a policy) URL3 (filled if instiution has a guideline) URL4 (filled if instiution has a followed up policy) Name of downloaded policy document (if applicable) Name of the downloaded guideline policy (if applicable) Name of the downloaded followed up policy (if applicable) Texts of Documents Documents were either HTML or PDF file. These were harvested full-text was extracted and put into a text file with the name of institution, and time stamp of original collection from the web concatenated into the name of the file. Tokenization of Documents In order to run LDA analysis the full-text documents were parsed and tokenized using spACy and NLTK. This process lemmatized the text, created bigrams, and removed stopwords. Each token file follows the same naming structure as the extracted full-text with the addtion of _tokens to the end of the filename. References Barzotto, M., Corradini, C., Fai, F., Labory, S., & Tomlinson, P. R. (2019). Enhancing innovative capabilities in lagging regions: An extra-regional collaborative approach to RIS3. Cambridge Journal of Regions, Economy and Society, 12(2), 213-232. https://doi.org/10.1093/cjres/rsz003 Marcus, A. A. (1981). Policy uncertainty and technological innovation. Academy of Management Review, 6(3), 443-448. https://doi.org/10.5465/amr.1981.4285783 Rodríguez‐Pose, A., & Wilkie, C. (2018). Innovating in less developed regions: what drives patenting in the lagging regions of Europe and North America. Growth and Change, 50(1), 4-37. https://doi.org/10.1111/grow.12280
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 | 0,003 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,007 | 0,001 |
| Communication savante | 0,009 | 0,004 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,007 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,642 | 0,472 |
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 ».