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Preparing children with diversity for the labor market with the help of technology

2024· dissertation· en· W7014495079 sur OpenAlexaboutno aff

Notice bibliographique

RevueRepositorio Institucional de la Universidad de Alicante (Universidad de Alicante) · 2024
Typedissertation
Langueen
DomaineBusiness, Management and Accounting
ThématiqueBusiness Law and Ethics
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésDiversity (politics)WorkforceMulticulturalismCultural diversityCompetitor analysisRace (biology)Ethnic group
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Diversity in today's labor market is a multidimensional construct that extends beyond race or ethnicity to encapsulate factors like gender, age, socioeconomic status, physical abilities, and even cognitive perspectives. As businesses and industries increasingly span across continents, adopting a more global footprint, the demand for a workforce that can adeptly navigate a diverse, multicultural setting becomes more pressing. Preparation for this reality is multifaceted—it's not merely about instilling cultural awareness or sensitivity. It also involves leveraging cutting-edge technology to ensure the younger generation is not only cognizant of diverse backgrounds but can actively engage, communicate, and synergize with individuals from different walks of life. This introductory exploration aims to shed light on the intricate interplay between technology and diversity training, emphasizing why it's crucial in readying children for the contemporary and future labor market. The onset of globalization, characterized by the increased interconnectedness of nations through trade, communication, and culture, has dramatically reshaped the contours of business operations. Companies, irrespective of their sizes, have transcended national boundaries to establish themselves on international platforms. A direct consequence of this is the rise of multicultural teams. A business might be headquartered in New York but could have its IT team in Bangalore and its customer support in Manila. This intricate global web implies that today's children won't just be contending with local competitors when they step into the job market. Instead, they'll be vying against a global talent pool. Furthermore, the essence of the modern labor market isn't just about technical proficiency. As important as hard skills are, soft skills, particularly those surrounding communication, empathy, and teamwork, have gained paramount importance. Employers are on the lookout for individuals who can seamlessly navigate the complexities of diverse teams. They seek professionals who can understand cultural nuances, adjust their communication styles in accordance with their audience, and essentially act as bridges, connecting different parts of a multicultural organization. The increased migration trends also add another layer to this dynamic. Major cities across the globe, be it Toronto, London, or Sydney, have turned into melting pots of cultures, drawing people from all over the world in search of better opportunities. This urban demographic shift underscores the need for cultural agility— the ability to quickly, comfortably, and effectively work in cross-cultural and diverse environments. Children need to be equipped not just to coexist but to actively collaborate with peers from different backgrounds, ideologies, and perspectives. It's not just the global corporations or cosmopolitan cities either. Even localized businesses recognize the value of diversity, understanding that varied perspectives lead to richer ideas, more innovative solutions, and a broader client appeal. A local startup, for instance, looking to expand its customer base, would immensely benefit from a team that reflects diverse backgrounds, capable of offering insights that cater to a more varied audience. All these realities combined present a clear message: the labor market is no longer what it used to be. It's more diverse, interconnected, and complex. As industries continue to evolve and the world becomes more enmeshed, the demands on the future workforce will only intensify. Preparing children for this reality requires a holistic approach, combining cultural education with technological proficiency, to ensure they remain agile, adaptable, and apt for the demands of the modern and future professional landscape.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Études des sciences et des technologies
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,807
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,002
Études des sciences et des technologies0,0020,001
Communication savante0,0000,001
Science ouverte0,0020,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,006
Tête enseignante GPT0,223
Écart entre enseignants0,217 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeThéorique ou conceptuel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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