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Record W907488360 · doi:10.20361/g23s41

All Fall Down: The Landslide Diary of Abby Roberts by J. Little

2014· article· en· W907488360 on OpenAlexvenueaboutno aff
Andrea Deakin

Bibliographic record

VenueThe Deakin Review of Children s Literature · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsBrotherAuntKindnessHistoryPrejudice (legal term)CompassionCharacter (mathematics)PsychoanalysisPsychologyArt historySociologyMedia studiesLawSocial psychologyPolitical science

Abstract

fetched live from OpenAlex

Little, Jean. All Fall Down: The Landslide Diary of Abby Roberts. Toronto: Scholastic Canada, 2014. Print.The Dear Canada Series is a strong, well-written series of novels bringing different periods of Canadian history to life through the voices of girls living at the time. There is a constant high quality of writing throughout the series and the books cover both moments of high drama, like the Halifax explosion, and also descriptions of the continuing stress of displacement and immigration.Jean Little is a fine writer whose descriptions vividly bring a scene to life and whose compassion exposes character and allows the reader to become one with her heroine.All Fall Down is the story of the Frank Slide in Alberta in 1902, but it does not begin there. We meet Abby and her family in Montreal and are thrown headlong into her story with the first sentence: “This morning my father was killed.” There has been an industrial accident and the family is left in turmoil. Here we begin to see the stresses Abby’s mother faces- no money, a child with Down Syndrome, and three other children to care for. Help comes from her mother’s brother who has opened a hotel in Frank, Alberta. He offers to take them all in. A three day train journey from Montreal takes them to Frank where their uncle and aunt greet them with kindness and concern. Little builds the situation in Frank; the prejudice against the Down Syndrome little brother, the prejudice, also against a friend Abby makes - Bird, a First Nations girl, and the changes in Abby’s older brother and sister as they, too, have to find a new place in the tiny community.The plot lines are skilfully woven- Abby’s growing skills and abilities, the family finding a place in the community, disease ,and strained relations with the First Nations people to the extent of ignoring a continual warning from Bird’s grandfather that the mountain would walk.Then the mountain walks.The first part of the book enables the reader to become so familiar with the family and the Frank community that the tragedy is all the more telling.All Fall Down is a strong engaging story, all the more effective because of the compassion with which a skilful writer, like Jean Little, has brought her people to life.Highly Recommended: 4 out of 4 stars Reviewer: Andrea DeakinAndrea has been involved with books since she was class librarian in Primary School, Student Librarian in Grammar School, student librarian for the Education Faculty when she was a student, and school librarian in schools both in England and in Canada, except for the first two years in Canada where she arrived in 1959. When she retired from teaching ( English and History) she was invited to review in February 1971, and continued to review for press, radio, and finally on the Internet (Deakin Newsletter from Okanagan College) until she retired in 2011. Forty years seemed sufficient- although she still cannot keep her nose out of good children's and YA fare.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.848
Threshold uncertainty score0.303

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.001
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0330.013

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.

Opus teacher head0.004
GPT teacher head0.228
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2014
Admission routes2
Has abstractyes

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