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Record W4313731313 · doi:10.1353/wlt.2023.0020

Ducks: Two Years in the Oil Sands by Kate Beaton

2023· article· en· W4313731313 on OpenAlexaboutno aff
Graziano Krätli

Bibliographic record

VenueWorld Literature Today · 2023
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsnot available
Fundersnot available
KeywordsTheme (computing)ArtHoganPsychologyHistoryArchaeologyComputer science

Abstract

fetched live from OpenAlex

Reviewed by: Ducks: Two Years in the Oil Sands by Kate Beaton Graziano Krätli KATE BEATON Ducks: Two Years in the Oil Sands Montreal. Drawn & Quarterly. 2022. 430 pages. IN THE FIRST two frames of Ducks, Kate Beaton introduces herself as the protagonist of this very personal and profoundly moving memoir: "This story starts in 2005. I am twenty-one years old." Then, almost as an afterthought: "This is me at twenty-one. I'm much older now, and three-dimensional." It is an arresting statement, complicated by an ingenious reference to the underlying theme of the book: the relationship between art (which in the case of a graphic artist is bidimensional) and life (whose three-dimensionality is the result of experience, knowledge, and trauma). This third dimension (painfully acquired and tamed into art) is what makes Ducks a very different—and, inevitably, a more mature and compelling—achievement than Hark! A Vagrant, the witty and hilarious webcomic that established Beaton's reputation and popularity. When, fresh out of college, Beaton left her native Cape Breton and took a job in the oil sands industry of northern Alberta, she could not imagine that the experience would be as affective and transformative as her keen statement, "Now I can't extract myself from having come," eloquently implies. Her only goal, after all, was to repay her student loans as quickly and uneventfully as possible. But in a world where men outnumber women fifty to one, female employees are alternately (or simultaneously) objects of desire and scrutiny, and variously subjected to discrimination, contempt, patronizing attitudes, sexual harassment, and assault. Inevitably, Beaton suffers the whole hypermasculinity catalog but survives the traumatic experience thanks to her candid, compassionate, inquiring attitude ("People do things here that they wouldn't do at home"); her quirky empathy ("I like you guys. But you're assholes"); and her growing commitment to comic art and determination to pursue it. Her progress is marked, symbolically, by three totemic encounters. The first is with relocated buffalo ("They put them on reclaimed old mine land, a company thing"), a veiled reference to the multiple displacements caused by the oil industry—of the workers who come from all over Canada and beyond but also of the Indigenous peoples and the wildlife whose livelihoods are impacted by the mining operations. The second is with a fox who has lost a front leg but keeps prowling around the warehouse at night. Beaton's anger (she chases the poor animal away by throwing snowballs at it) may be surprising but makes sense as a presage of her own coming injury. The third, and most significant, encounter is the news that, in April 2008, 1,600 ducks died after landing on a Syncrude tailings pond north of Fort McMurray, one of the sites at which Beaton worked. This, and a YouTube video of an elder Cree woman speaking out against the oil extraction industry, raises Beaton's awareness of the abuse from a personal to a political level. As we reach the end of the book, we realize that the ducks of the title represent a double tribute—to the birds who died as well as to Beaton herself ("ducky" for her older coworkers), who was able to take off and fly away from the bitumen. Graziano Krätli North Haven, Connecticut Copyright © 2023 World Literature Today and the Board of Regents of the University of Oklahoma

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)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.720
Threshold uncertainty score0.557

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.003
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0530.014

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 head0.007
GPT teacher head0.273
Teacher spread0.265 · 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
GenreOther

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

Citations1
Published2023
Admission routes1
Has abstractyes

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