Multidisciplinary Training to Meet the Legal Needs of Intellectual Property Start-Ups
Notice bibliographique
Résumé
This report explored whether multidisciplinary programming (e.g., law, business, and science faculty collaboration) in universities can assist in bringing meaningful and affordable intellectual property (IP) knowledge to IP start-ups. An IP start-up refers to a start-up company with an IP-intensive component (e.g., scientific innovation) that can be commercialized (Tawfik, 2016). Research completed by Tawfik (2016) has found that there is a “fault line in Canada’s innovation capacity” as Canada has not taken the steps to actively ensure that IP start-ups are able to successfully commercialize on their IP. Consequently, this report has taken a critical look at one of the recommendations put forward by Tawfik (2016), which is to support early stage IP start-ups through multidisciplinary programming in universities. The researcher, a JD/MBA student at the University of Windsor, chose to explore this recommendation by observing business students as they provided consulting services to IP start-ups being worked on by science students. Through participant observation (Kawulich, 2005), the researcher was able to become fully integrated in the consulting process and privately flag relevant legal issues that were either addressed or missed by the business students. After analyzing the data collected, the researcher found that both the science and business students did not have a working knowledge of IP and the complexity of developing a comprehensive IP strategy. Nonetheless, the business students were able to provide deliverables that addressed some of the relevant IP legal issues after seeking legal information from the researcher. Thus, a conclusion was made that the unique skill sets of business, law, and science, technology, engineering, and math (STEM) faculties, will be shared with all students engaged in multidisciplinary programming. Specifically, it is believed that business students would be able to learn how to flag relevant IP legal issues by collaborating fully with law students in multidisciplinary programming during their university training. Ideally, the business students will later be able to flag relevant legal issues when working with IP start-ups in practice so that they can engage the services of a lawyer early on in the commercialization process or not need to at all.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 tête enseignante, 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 ».