Bibliographic record
Abstract
Being parents and being human: building hope for our children in a fragile world. Environmental catastrophes, pandemics, antibiotic resistance, institutionalized injustice, and war: in a world so out of balance, what does it take—or even mean—to be a good parent? This book is one woman's search for an answer, as a moral philosopher, activist, and mother. Drawing on the insights of philosophy and the experience of parent activists, Elizabeth Cripps calls for parents to think radically about exactly what we owe our children—and everyone else. She shows how our children's needs are inseparable from the fate of the earth and the fortunes of others and how much is at stake in parenting today. And she asks the hardest question: should we have kids at all? Timely and thoughtful, Parenting on Earth extends a challenge to anyone raising children in a troubled world—and with it, a vision of hope for our children's future. Cripps envisions a world where kids can prosper and grow—a just world, with thriving social systems and ecosystems, where future generations can flourish and all children can lead a decent life. She explains, with bracing clarity, why those raising kids today should be a force for change and bring up their children to do the same. Hard as this can be, in the face of political gridlock, ecoanxiety, and general daily grind, the tools of philosophy and psychology can help us find a way.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.069 | 0.031 |
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".