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Notice bibliographique
Résumé
Across the world, universities have just emerged from the shadow of the pandemic. Nonetheless, in the wake of campus reopening, university administrators must acknowledge that restoring normalcy following the pandemic will present formidable challenges. The realm of academia is already undergoing a significant paradigm shift due to the need for business reinvention. Heightened workplace requisites and evolving student aspirations substantially disrupt the worldwide higher education framework [1]. \nIn recent years, a pronounced focus has been establishing stronger ties between academia and industry [2], [3]. As an external network for companies, the university plays a pivotal role in facilitating the advancement and growth of the design industry. The imperative for effective collaboration between academia and industry has grown increasingly significant, given the substantial paradigm shift within the design sectors. Nevertheless, a persistent disparity exists between the industry's demands and the offerings of universities [4]. Preparing a competent workforce is crucial for sustaining a company's internal capabilities, necessitating ongoing and constructive dialogue between academia and the professional sphere. Rather than remaining confined within an isolated academic realm, universities must undergo transformation and reinvention to align with the industry's emerging realities, thereby translating theoretical knowledge into practical applications that address contemporary industrial concerns and equipping graduates with the requisite skills and competencies for the workforce. \nAccording to a 2016 study conducted by Bocconi University, a notable correlation between skill mismatch and substantial GDP declines and elevated unemployment rates within the country has been established. Given the inherent differences in objectives between universities and industries, difficulties in comprehending and aligning common goals are bound to arise [2]. Achieving a shared contextual understanding among diverse stakeholders has emerged as a critical challenge in bridging the gap between academia and the corporate sector [4]. Typically, academia prioritizes the theoretical aspects, while industry focuses on profit-driven product development. However, when these two realms converge in a synergistic collaborative relationship, they can discover common ground and establish a mutually beneficial, enduring outcome. \nThis paper examines the gap between the design field in academia and industry, aiming to shed light on potential solutions for strengthening the ties between these two sectors. The authors present a design project emphasizing the synergy between universities and companies, illustrating how such initiatives can effectively bridge the university-company gap. Through their distinct perspectives, the authors offer novel insights into the interplay between academic research and design practice, elucidating strategies to integrate these domains to foster innovation and advance knowledge. The authors hope the experiences gained from the project can offer a valuable reference point for fellow researchers in related disciplines to explore the design practice better, ultimately resulting in more impactful outcomes.
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.
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 | 0,006 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,003 | 0,013 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,009 | 0,004 |
| Science ouverte | 0,005 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,017 | 0,331 |
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 découle