Bibliographic record
Abstract
Less, Emma. “Dentists.” Real-life Superheroes. Amicus Publishing, 2018. Aimed at emergent readers, this Real-life Superheroes series is intended to inform children of the ways community helpers do their jobs, understand what the jobs mean, inspire readers, and expose readers to vocabulary and action images specific to occupations in the spotlight. This is a review of three out of twelve Real-life Superheroes books. Other occupations in the series include chefs, librarians, construction workers, farmers, firefighters, mechanics, police officers, teachers, and veterinarians. Each book begins with the relevant job title and a purpose statement. The “Dentists” and “Doctors” books have health-promotion statements while the “Nurses” introductory statement is limited to an illness focus. Health promotion is a primary focus of these three professions and it is incorrect to limit nursing to an illness focus in the primary introduction. Also, on the first pages of the “Dentists” and “Doctors” books the author says “They [Dentists/Doctors] are busy,” while the “Nurses” book does not include the same statement. Further, the “Doctors” book includes a “Maybe you will be a Doctor” statement, while the “Dentists,” and “Nurses” books do not. These statements should be included in all the books. The books adequately introduce subject specific vocabulary and use child-centered action images. The images are high quality, and feature real-world tools (needles, syringes, stethoscopes, electronic vital signs monitors, etc.). Regarding the pictures of the professionals, there could have been greater effort to demonstrate diversity, to ensure all children could see themselves reflected in the images. For example, only one of seven nurses shown is male, reinforcing gender stereotypes related to this profession. In the “Dentists” and “Doctors” books the images show a more diverse picture of the professions, when race and gender is considered. The last page of each book is dedicated to tools seen in the workplace and these would encourage curious readers to ask questions about the profession. As a tool to introduce early readers to health care jobs and inspire them to think of themselves in these roles, the books fall short; specifically, they do not give a full and accurate account of job tasks and job relationships. For example, the books mention the nurse-doctor team but do not mention the dentist-dental hygienist team. Overall, these books are of limited use as they do little to inspire children to imagine themselves in these roles, and they lack accurate job descriptions. Not Recommended: 1 out of 4 StarsReviewer: Tabatha Plesuk Tabatha Plesuk, is a first year MLIS Student at the University of Alberta (who spends free time teaching dance to children ages three to fourteen) with an enthusiasm for children’s books.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.449 | 0.435 |
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".