Bibliographic record
Abstract
Klassen, Jon. I Want My Hat Back. Somerville, Mass. : Candlewick Press, 2011. Print. Jon Klassen further develops his distinctive and carefully honed aesthetic in I Want My Hat Back, the first children’s book he has both illustrated and written. His illustrations for 2010’s visually complex yet cohesive Cat’s Night Out deservedly won the Governor General’s award for English language children’s illustration. [Reviewed here in Vol.1 no.2 (2011).] Klassen has a very well conceived style that seems to perfectly encompass what current sensibilities would deem the best of design from the 1960s and early 1970s. As a writer, he has a sharp sense of humour that comfortably inhabits his visual style. Both expressions are arch, dry and irreverent. I Want My Hat Back is, without question, a great looking book that adeptly functions on a number of aesthetic levels. The issue remains, however, of how it functions as a visual and textual narrative for children and in order to discuss that clearly I must provide a SPOILER ALERT: In I Want My Hat Back the rabbit who has absconded with the hat in question is eaten in retribution by a bear. The fact of this dire revenge is conveyed very amusingly but obliquely. So obliquely that it seems unlikely that a child would be able to understand (perhaps mercifully) what had happened as the bear denies that he knows what has become of the rabbit. This presented an excellent opportunity to experiment on my children by reading them I Want My Hat Back and observing their reactions. The two year old was most distressed by the fact of the missing hat and relieved at its recovery. He seemed to have grasped that the bear eats the rabbit at the end but was unconcerned. The five year old, however, took the bear at his word and has no idea what happened to the rabbit. Perhaps the two year old in the initial stage of language comprehension had to hear and interpret the bear’s words more literally than the five year old who, while she can understand language in a more nuanced way, can’t interpret the implications that lie beyond what the bear says? Fascinating! Highly recommended: 4 out of 4 stars Reviewer: Matilda RocheMatilda spends her days lavishing attention on the University of Alberta’s metadata but children’s illustrated books, literature for young adults and graphic novels also make her heart sing. Her reviews benefit from the critical influence of a four year old daughter and a one year old son – both geniuses. Matilda’s super power is the ability to read comic books aloud.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".