Bibliographic record
Abstract
Condie, Ally. 2016. Summerlost. New York: Dutton Children’s Books. Print.Cedar’s Mother has brought Cedar and her brother to Iron Creek, her hometown, for the summer. They have bought a house that her mother intends to rent over the rest of the year and keep it for them as a summer home. For Cedar, this is not just any ordinary summer vacation. Only a year ago, her father and brother Ben were killed in a car accident with a drunk driver. Haunted by memories of a father and brother no longer with them, the family is struggling to move forward, each of them dealing with the changes and the grief. Shortly after they arrive, Cedar finds a friend in Leo, a boy her age who is working at the local Shakespeare festival. Through Leo, she manages to get a job at the festival as well. She also learns about the legendary Lisette Chamberlain, a local girl who got her start in the festival, and later moved on to a career in Hollywood. As with many cases of stardom, Lisette had several romances and met a tragic end, when she was found dead in a local hotel. Cedar is fascinated by Chamberlain’s story, and she and Leo concoct a plan to offer private “Lisette” tours for festivalgoers, for extra money. Hiding their tours from festival officials and their parents prove difficult and then Cedar stumbles across a detail that might shed light on the mystery of Chamberlain’s death.Summerlost is a surprisingly layered story about a young girl’s formative summer. Intermixed between the sleuth work of Cedar and Leo, is the struggle of a family coming to terms with an immeasurable loss. Cedar must not only manage her own feelings of loss and confusion, but she is growing old enough to see her mother’s and brother’s struggles as well. The friendship between Leo and Cedar is quite wonderful, platonic and sincere. I will admit the Lisette Chamberlain mystery, while compelling in the beginning, became a bit tedious and felt anticlimactic in the end. Nevertheless, the story is touching mix of daydreams and hard truths. This story will appeal to both young and old. The young will see themselves in Cedar as they are now and adults will be taken back to their own childhoods, to relive their own bittersweet summers.Recommended: 3 out of 4 starsReviewer: Hanne PearceHanne Pearce has worked at the University of Alberta Libraries since 2004. Aside from being an avid reader, she has continuing interests in writing, photography, graphic design and knitting.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.485 | 0.374 |
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".