Family and Eco-citizenship
Bibliographic record
Abstract
Research framework: Although the family is typically the place where socialization and learning begin, and where values, practices and cultures are handed down, the ways in which eco-citizenship is taught within the family remain underexplored in current research.Objectives: This introductory article, along with the other articles in this special issue, explores various aspects of the relationship between family and eco-citizenship.Methodology: This article is based on a partial review of the humanities and social sciences literature on the subject.Results: The introductory article and the texts that make up the special issue shed light on the ways in which family dynamics are changing, on children's and young people's involvement in environmental action, and on the role of institutions in the development of eco-citizenship.Conclusion: The social processes by which eco-citizenship is constructed, and the transformations that take place within families in response to eco-citizen actions, underline the need for practices and lifestyle changes that involve a diverse array of actors, including young people, their families, institutional bodies and policymakers. The scientific community needs to pay more attention to this issue, as literature on the subject is still scarce.Contribution: In addition to providing some insights into the relationship between the family and eco-citizenship, this article suggests avenues for research in cultural and international contexts, issues of social and environmental justice, and the roles played by media and digital technology in fostering eco-citizenship.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".