Bibliographic record
Abstract
Urrutia, Maria. Who will save my planet? Toronto: Tundra Books, 2012. Print.This volume appears to be a republication of a 2007 imprint from the author’s own publishing house, Tecolate Books, in Mexico. Although Tundra recognizes support from the Canada Council for the Arts, there appears to be no specific Canadian content in this book. There is no text and the images are the work of several different photographers. Urrutia’s contribution to the work appears to be the title and the selection and pairing of the images. The book is designed for children ages 7+ and consists of 14 pairs of unadorned, borderless photographs. Each spread of two images shows something environmentally negative on the left and a corresponding positive image on the right. However, without text, the viewer is left to draw their own conclusions about what message is intended. Many of the images have several potential interpretations, particularly for viewers coming from a different environment. For example, the opening pair of images shows fire in the canopy of a tropical forest, presumably implying that people are burning the forest. However in Canada, lightning is naturally one of the primary causes of forest fires which is a natural part of the forest’s life cycle. In the second set of images, someone is cutting down a tree, but it is the only one being felled. The rest of the forest appears to be undisturbed. An image of a clear-cut would have conveyed a much more obvious message. The second last pair show garbage strewn along a path and the images are a garbage can overflowing with garbage, with a plastic water bottle prominently placed on top. Bottled water is one of the least environmentally friendly things on the planet. Is the message that producing huge volumes of unnecessary garbage is fine as long as you put it in the garbage can? Many of the images are high quality. An image of a seal with the rope embedded in the flesh around its shoulders is particularly effective. However, the selection and combination of images, as a whole, reminds me of posters at a fourth grade science fair. The difference is that the fourth graders usually add captions and introductory paragraphs so that their messages are clear. While environmental damage anywhere is important, this book would have been more effective for the Canadian market had it incorporated images of environmental problems found in the Canadian environment. Recommended with reservation: 2 stars out of 4 Reviewer: Sandy CampbellSandy is a Health Sciences Librarian at the University of Alberta, who has written hundreds of book reviews across many disciplines. Sandy thinks that sharing books with children is one of the greatest gifts anyone can give.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.065 | 0.061 |
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".