Społeczne i ekonomiczne konsekwencje migracji zewnętrznych mieszkańców obszarów wiejskich
Bibliographic record
Abstract
The article presents the outcomes of rural dwellers’ migrations in the economic and social aspect. Apart from defining the phenomenon of external migration against the background of current social trends, also a review of motives for migration including the push factors (home country) and the pull factors (host country) in three aspects: economic-demographic, political and socio-cultural are presented. Furthermore, the economic effects of population flows from the perspective of functioning of the countries affected by mass emigration are discussed extensively. The empirical part of the article is focused on an analysis of results of studies conducted on a group of approximately 100 person involved in economic emigration. Respondents, whose permanent place of residence is South- Eastern part of Poland, have most frequently chosen the USA or Canada as the target country, whereas in Europe they migrated to Ireland, Germany and the United Kingdom. Willingness to improve their material status, the threatening unemployment or continuation of education prevailed among the reasons for migration. These elements were also most frequently indicated as positive outcomes of the decisions, whereas an additional asset of the emigration was an improvement of one’s status in the society or better chances for professional promotion, but also a cognitive motive. On the other hand the respondents pointed to negative results of migration, among which social effects like trauma caused by prolonged separation from the family, loosened family bonds or health injuries, and in the economic aspect the considerable costs incurred by the mobility. / Synopsis. Artykuł prezentuje skutki migracji ludności obszarów wiejskich w aspekcie ekonomicznym i społecznym. W opracowaniu, poza zdefiniowaniem zjawiska migracji zewnętrznych na tle współczesnych tendencji społecznych, zaprezentowano zestawienie motywów migracyjnych z uwzględnieniem czynników wypychających (kraj macierzysty) oraz przyciągających (kraj goszczący) w odniesieniu do trzech płaszczyzn: ekonomiczno-demograficznej, politycznej i społeczno-kulturowej. W dalszej kolejności sporo miejsca poświęcono ekonomicznym skutkom przepływu ludności z punktu widzenia funkcjonowania państw dotkniętych masową migracją. W części empirycznej skupiono się na analizie wyników badań przeprowadzonych metodą ankietową na grupie blisko 100 osób podejmujących zagraniczne wyjazdy zarobkowe.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".