Religion as a Human Right and a Security Threat—Investigating Young Adults’ Experiences of Religion in Finland
Bibliographic record
Abstract
The emergence of religiously motivated terrorist attacks and the increasing xenophobia expressed in Europe concern religions in many ways. Questions related to religion also lie at the core of educational aims and practices used to create national cohesion and understanding about different types of values and worldviews. However, despite the topicality of the issue, we have little knowledge about the ways in which young adults experience religions in a secular state. In order to contribute to the discussion regarding the relationships between religion, nationality, security, and education, this study focuses on investigating how politically active young adults experience the role of religions in Finnish society. The qualitative data of this study were collected from young adults (18–30-year-olds) through an online questionnaire distributed through political youth organisations. The content analysis of the responses (altogether 250 respondents) identified five main orientations towards religions. The findings highlight the importance of providing young people with education about different faiths and worldviews for reducing prejudices, especially those related to Islam. The findings also highlight the need to address in education and society the possible but not as self-evident relationship between violence and religion, and to do this more explicitly than is currently done.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".