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Record W4313589903 · doi:10.29173/cjfy29893

Book Review of Eckler, Rebecca. (2019). Blissfully Blended Bullshit: The Uncomfortable Truth of Blending Families. Toronto: Dundurn Press.

2023· article· fr· W4313589903 on OpenAlexaffvenueabout
Jakub Tompalski

Bibliographic record

VenueCanadian Journal of Family and Youth / Le Journal Canadien de Famille et de la Jeunesse · 2023
Typearticle
Languagefr
FieldEconomics, Econometrics and Finance
TopicGlobal Socioeconomic and Political Dynamics
Canadian institutionsMacEwan University
Fundersnot available
KeywordsArtArt history

Abstract

fetched live from OpenAlex

book, "Blissfully Blended Bullshit," is a biography of her experience of creating a blended family where her new boyfriend, along with his two daughters, moves into the home she currently lives in with her daughter Rowan.Eckler does not rely on statistics, nor any scientific data related to blended families to convey what life is like in such a situation.Instead, she relies on her experience to convey what could occur in such a relationship.The author's perspective, along with advice Eckler receives from friends, is used to convey how at the beginning, things may seem perfect in a blended family, but over time things are not exactly how they seem.The further they get into the relationship, the more she realizes that things are not as perfect as they seem.Her realization that love is not equal, along with issues involving finances, and finally realizing that people change when a relationship ends, and things are not going as well as they believed.The book is organized ideally to showcase the different points in their relationship and the effects that it has on her.Eckler describes that at the beginning of their relationship, they did not prepare any rules or financial responsibilities because they "are so in love, none of that seems to matter" (p.29).Everything felt right in the author's mind, and they had all spent time together, so the possible

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.414
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.240
Teacher spread0.223 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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
Published2023
Admission routes3
Has abstractyes

Explore more

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