Notice bibliographique
Résumé
INTRODUCTION In 2001 a chief economist at Goldman Sachs, Jim O'Neill, theorized that by 2035, the combined GDP of the BRIC economies, Brazil, Russia, India and China, would exceed the combined GDP of the G7 countries (Canada, France, Germany, Italy, Japan, U.K., and the U.S.) (O'Neill, 2001). It was further predicted that by at least 2050, the BRIC bloc of emerging markets will dominate the global economy (Wilson and Purushothaman, 2003). Accepting the validity of these economic predictions, this article considers the implications of BRIC market dominance for the global private business sector in the field of cybersecurity. Specifically, based upon a demonstrable lag in the development of the respective BRIC domestic legal infrastructures in the fields of cybersecurity and the protection of intellectual property, how should business assess the degree of asset risk exposure attendant to a market entry strategy aimed at increased BRIC penetration? Simply put, how cybersafe are the BRICs for global business? In order to gauge asset risk exposure due to unauthorized cyber-penetration of intellectual property, a species of global theft, the article examines the magnitude of the global economic threat posed by cybercrime and the existing international and domestic legal intellectual property (IP) protections afforded foreign private sector companies doing business in each respective BRIC country. The article concludes that intellectual property is not cybersecure because BRIC countries do not offer concise and meaningful legal protections in the form of enforceable legal rights nor do these countries demonstrate a present or future commitment to multilateral treaty initiatives aimed at minimizing economic risk. Thus, any business contemplating increased market penetration into the BRIC bloc should factor in both the risk to its internal systems security and/or the possibility of conversion of its trade secret and copyright assets through unauthorized cyber-penetration. The weight to be accorded to this cybersecurity risk assessment factor will depend upon several variables, including but not limited to: the type of intellectual property, the measures required to adequately protect the interest given the choice of market entry strategy, and the asset value of the interest to the company. Generally, risk assessment is undertaken to achieve efficient risk management. Indeed, the management of international business is frequently characterized as the management of risk (Schaffer, Earle and Agusti, 2008). This article contributes to the assessment of risk in three ways. First, provides increased awareness of a particular global economic threat to enable the private sector to engage in a smarter cost/benefit analysis about competing market entry strategies. Second, provides a dialogue helpful to the analysis of the choice of the appropriate market entry strategy given the nature and complexity of the risk. Finally, the private sector, as a crucial stakeholder, can assume a more efficient participatory role in the development of economic and legal policies given a greater understanding of this global business problem. Just as O'Neill prognosticated that it is time for the world to build better global economic BRICs, follows that is time for the world to build better global cybersafe BRICs in the interest of global commerce. This article is also intended to expand the prior research of Bird and Cahoy which focuses upon the failure of BRIC nations to enforce internal domestic laws prohibiting the unlawful conversion of intellectual property rights in the pharmaceutical industry. The research concludes that the failure of enforcement of patent protections by BRIC nations undermines global competitiveness (Bird, 2006; Bird and Cahoy, 2007). The more recent research of Kapczynski revisits India's pharmaceutical sector concluding that India has managed to side step the plain intent of the TRIPS treaty (Agreement on Trade Related Aspects of Intellectual Property Rights)1 which is to afford the foreign private business sector adequate intellectual property protection (Kapczynski, 2009). …
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 | 0,000 |
| 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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 ».