Book Review of Eckler, Rebecca. (2019). Blissfully Blended Bullshit: The Uncomfortable Truth of Blending Families. Toronto: Dundurn Press.
Bibliographic record
Abstract
Blissfully Blended Bullshit: The Uncomfortable Truth of Blending Families", is a raw retelling of Eckler's personal experience of being in a blended family that despite its best efforts, could not work out.Eckler, through the usage of humour and blunt language, describes the issues she faced within her blended family.With already being a single mother to her beloved daughter, Rowan, pregnant with another child, and opening her home up to her new partner as well as his two daughters and all of their furniture, Eckler brings us along in her journey of grappling with all of these changes coupled with all of the complications that come with blending.Eckler's straightforward retelling of her own experience of blending families intertwined with anecdotes of friends and acquaintances who've experienced similar problems bring forth an unfiltered and intense view of the ugliness that can arise from blending.A reoccurring theme, although possibly unintentional, is Eckler's hypocrisy regarding her behaviour compared to the behaviour of her partner and his family.Despite the author beginning the book by proclaiming that she will not give an unbiased narrative where she comes across as roses and rainbows and her family comes across as assholes, she does just that.(p.14).From the beginning, Eckler retells many occasions throughout her blending experience where those who are not biologically related to her face harsher criticism for doing the same things she and her biolo-
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.090 | 0.056 |
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".