FEATURES AND TRENDS CONTEMPORARY PROCESSES OF POPULATION REPRODUCTION IN TERNOPIL
Notice bibliographique
Résumé
The article presents the results of the study of the demographic situation in Ternopil. The sex-age structure of the population and indicators that determine the course of population reproduction processes: fertility, mortality and natural increase are characterized. Research has shown that at the beginning of 2021 in Ternopil there were 223,8 thousand inhabitants (21,5 % of the total population of Ternopil region). Compared to 2001, the population decreased by 3,9 thousand people, or 1,7%. In 2020, for the first time in Ternopil, the number of deaths exceeded the number of newborns – a natural increase, thus, fell below zero and became negative (-1,5). The slight increase in the number of Ternopil residents, which has been observed in the last two years, was solely due to internal migration. One of the reasons for this is the high level of unemployment in rural areas of the region, from where migration to the regional center takes place in order to find employment and improve the quality of life. Over the last ten years, there has been a negative trend towards increasing the demographic burden on the working population of persons of working age and post-working age, and at the beginning of 2021 these figures were, respectively, 246 and 432 persons per 1,000 working population. In recent years, there has been a fairly marked decline in the overall birth rate. In 2020, it was at the level of 9 ‰, which is a quarter (25,6 %) less than in 2014. The total fertility rate at the beginning of 2021 was at the level of 11 children per 10 women, which is not enough for simple reproduction of the population cities; the current level of this indicator in Ternopil provides for the replacement of generations by only 52,2 %. Over the last twenty years, mortality rates in Ternopil, as well as in Ternopil region as a whole, have been constantly changing and until 2005 had a steady upward trend, then the mortality rate stabilized at 8,3-8,6 ‰, and since 2007 The indicator started to gradually decrease (to 7,7 ‰), but since 2011 the growth trend has been observed again. This increase in mortality is still observed. In 2020, this indicator reached the maximum mark for the entire observation period (2001-2020) – 10,6 ‰. It is noteworthy that the death rate in Ternopil has always been lower than in the Ternopil region as a whole. This is due to a number of factors, primarily the fact that in the age structure of the population of Ternopil is much smaller share of the elderly (12,5 %) than in the region as a whole (15,6 %), which have the highest mortality rates. Improving the demographic situation in Ternopil is possible under several conditions: increasing real incomes and overcoming poverty; reducing unemployment and shadow employment, reforming the social assistance system in order to strengthen its targeting of socially vulnerable groups, improving the quality and accessibility of preventive and medical care, stimulating the birth rate, spreading healthy living standards, etc. The complexity of solving the demographic problems that have developed in Ternopil is due to the significant inertia of demographic processes, and therefore the longer their solution is delayed, the larger they will become. Given the current demographic situation in Ternopil, it is important to predict the number and gender and age structure of the population in the future. Therefore, in the medium and long-term forecasting of the qualitative and quantitative composition of the city’s population, it is necessary to identify priority measures to mitigate negative demographic trends, as well as to study the dynamics of the working population, because this age group will be the main labor force. further socio-economic development of Ternopil. Key words: demographic situation, population size, depopulation, population aging, fertility, mortality.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».