The Impact of the Foreign-Speaking Population of Estonia on the Development of Highly Innovative Services
Notice bibliographique
Résumé
<p><span dir="ltr">Aim and tasks.</span> <span dir="ltr">To determine the influence of non-Estonian-speaking population on the development</span><br><span dir="ltr">of network structures in the highly innovative services sector of Estonia. To achieve the objective of</span><br><span dir="ltr">the study, the following objectives were set: analysis of literary sources on the topic of the study;</span><br><span dir="ltr">determine the role of the non-Estonian-speaking population in the sector of highly innovative services</span><br><span dir="ltr">of Estonia; conduct a correlation and regression analysis of indicators characterizing the influence of the</span><br><span dir="ltr">non-Estonian-speaking population of Estonia on network structures in the sector of highly innovative</span><br><span dir="ltr">services.</span> <span dir="ltr">Methods.</span> <span dir="ltr">To determine network structures, an indicator from the collection “Science.</span><br><span dir="ltr">Technology.Innovation” of the Estonian statistical service was used, which characterizes the number</span><br><span dir="ltr">of enterprises that had partners in the field of innovation activities. Data on cooperation between</span><br><span dir="ltr">Estonian organizations is published for a two-year period. In the correlation and regression analysis,</span><br><span dir="ltr">the data referred to the last year in the period. As a characteristic of the non-Estonian-speaking</span><br><span dir="ltr">population, indicators of the population employed in the economy were used.</span> <span dir="ltr">Results.</span> <span dir="ltr">The role of the</span><br><span dir="ltr">non-Estonian-speaking population in the Estonian economy, including in the Estonian highly innovative</span><br><span dir="ltr">services sector, was analyzed. During the period under review, a third of the employed population</span><br><span dir="ltr">of Estonia with higher education are non-Estonian-speaking. A quarter of all employed specialists in</span><br><span dir="ltr">the top and middle management levels are also non-Estonian-speaking. In the sectors “Information</span><br><span dir="ltr">and Communication” and “Professional, Scientific and Technical Activities”, the non-Estonian-speaking</span><br><span dir="ltr">population makes up 1/5 of all employed. Based on the results of the regression analysis, a statistically</span><br><span dir="ltr">significant and reliable regression model was identified, indicating that the development of network</span><br><span dir="ltr">structures in the information and computer services sector is influenced by Russian-speaking specialists</span><br><span dir="ltr">at the “Manager” level.</span> <span dir="ltr">Conclusions.</span> <span dir="ltr">Despite the aggressive Estonianisation policy pursued by the</span><br><span dir="ltr">Estonian leadership, the non-Estonian speaking population, especially the Russian speaking population,</span><br><span dir="ltr">plays an important role in key sectors of the Estonian economy. The issue of linguistic security and</span><br><span dir="ltr">diversity is an important element of the nation’s self-identification, so ill-considered decisions can lead</span><br><span dir="ltr">to increased social tension. At the same time, limiting the rights of a third of the population can not only</span><br><span dir="ltr">aggravate social tension in society, but also have a negative impact on the economic development of</span><br><span dir="ltr">the entire country.</span></p>
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 | 0,003 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,003 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».