Bibliographic record
Abstract
Introduction The story of the legendary character Peter Pan living in Neverland begins with such words, ‘All children, except one, grow up’ (Barrie, 1911, p 3). J.M. Barrie's character Peter Pan is a child who will never grow up. This legendary story promulgated the myth that, while it was the fate of all children to grow old, this was not the case with Peter Pan. In reality, the children of Turkey today will be part of the future demographic trend towards rapid population ageing. Turkey is neither a Neverland nor are its young people endowed with the eternal youth of Peter Pan. While Turkey, at the present time, has a predominantly young and dynamic population, this will change in the near future due to declining fertility rates combined with increasing numbers of people living into old age. Turkey must accept that it, too, is becoming part of the worldwide trend towards population ageing. In the light of the demographic revolution in the age composition of world populations, it seems reasonable and timely, therefore, for Turkey to investigate the following research questions: what is the course of ageing in its barest form and basic meaning in Turkey? What are the conditions of older adults based on sociological factors such as daily life, gender, marital status, education, work and income, health, and religion and ethnicity? What is the perspective of the state in Turkey towards ageing in the realm of social policy? Drawing on the preceding information and questions, the issues of older people and ageing in Turkey are discussed in this chapter in terms of four main themes. First, the chapter begins with a discussion of the current dynamics relating to the demographics of population change in Turkey, and likely emerging challenges and future trends. Attention is thereby focused on comparing social change processes in Turkey with those in Europe by way of using seven sub-themes, namely: urbanisation, gender, marital status, education, work and income, health, religion and ethnicity. It is also the aim to highlight the emerging image of older people in Turkish society, and how the ageing process is being perceived within the wider societal context. In order to foster a meaningful discussion on the preceding issues it was decided to source and analyse raw data from a number of relevant research projects.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".