In- <i>Conceivable Futures</i> : Climate Change and Reproductive Decision Making Among Childfree North Americans
Bibliographic record
Abstract
This paper engages in a content analysis of public testimonies available through the Conceivable Future project, a network of individuals from the United States and Canada who seek to bring awareness to the threat climate change poses to reproductive justice. How are these individuals navigating reproductive decision making amid the climate crisis? Specifically focusing on individuals who express that they are choosing not to have children, we explore how emotional experiences, family planning, and environmental concern collide within the Anthropocene. Analysis of testimonies revealed a number of themes. Most people struggled with ethical questions about what it means to be accountable to and responsible for future generations in a warming world. Their concerns were tied to visions of future climate apocalypse and, implicitly and explicitly, to recognition of their own privileges living in North America. Many encountered some form of stigma or social pressure from family, friends, and/or broader society about their choice to remain childfree, sentiments more strongly expressed by women. Ultimately, individuals forgoing having kids express motivations rooted in love and the hope that they can channel their energies into alternative forms of caregiving and/or activism.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".