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Record W2029674673 · doi:10.1353/crv.2006.0011

"Taking Them to the Moon in a Station Wagon": An Interview with Ann-Marie MacDonald

2005· article· en· W2029674673 on OpenAlexvenueno aff
Melanie Lee Lockhart, Ann-Marie MacDonald

Bibliographic record

VenueCanadian Review of American Studies · 2005
Typearticle
Languageen
FieldArts and Humanities
TopicAmerican and British Literature Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsSympathyPrideAppealIdeal (ethics)SociologyLawPsychoanalysisMedia studiesPsychologyPolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

"Taking Them to the Moon in a Station Wagon":An Interview with Ann-Marie MacDonald Melanie Lee Lockhart (bio) (by telephone, May 11, 1998) Melanie Lee Lockhart: I've heard you characterize your project as the "fight to make the world larger." Could you touch on the strategies you use to appeal to a wider audience—how you bring other points of view into the body of your work? Ann-Marie MacDonald: I don't try to create an ideal world. I don't try to fix the world, in my novel for example. I try to include as much of what I see being there as possible, and enter into sympathy with the various points of view. For example, entering into sympathy with James and his destructive desires and ambitions. Entering into sympathy with Teresa and her rage and her racism and her pride—she has stuff in common with James at that level. And we can definitely say, well, she has reason and he doesn't—we could argue that. But I try not to apologize or to justify points of view, but to illuminate them. I'm not trying to change the characters, to change James into somebody who won't abuse his daughter. I'm not trying to change Teresa—I mean, she shoots somebody. I'm not trying to make anyone better or worse than they really are. But try to see that their actions will have results and repercussions. And somewhere, symphonically, each of them is playing an instrument. And they have no idea that they are playing in the same orchestra. They have no idea that they're all—and I guess this is my vision as a storyteller—that, wittingly or unwittingly, they are all contributing to the narrative and to the various explosions of the narrative. For example, Frances being shot is a process that [End Page 139] began when her older sister met Rose in New York City. It continued when Frances started to try to seduce Ginger. It was compounded when Ginger heard Rose play the piano in Harlem when Rose was masquerading as a man. All the steps are there. Basically, the Luvovitzes and the Taylors and Teresa, the black people, the Jewish people, the Lebanese people, the white people, you know, the Anglo people, many of them share the same prejudices and the very same self-images. And I like to show that because it's ironic. And many of their clannish qualities are very endearing, and many of us can identify with them, but it's also necessary that they be put up against pluralism and democracy and individuality, and the right of people to be individuals, not just products of their culture, or of the old country. And it's in that collision, the tension between the old country, the family, the racial, cultural, clannish values, colliding with the contemporary world in a way that the secular world, the world that says you're an individual no matter what colour you are, it doesn't matter. And the irony, of course, is that it matters, not just because you'll be discriminated against, but because that gives you power too! It gives you identity. It does matter. But it's in that tension and it's in that collision that I find the stories. Not wanting to lose what you've been born with, what your parents have given you, but knowing that you have to lose some of it in order to embrace what's going to be yours. And to be part of a secular, democratic culture, you move out of that inner ring—but you try to keep both things going. MLL: Would you say that's what your writing is for—to bring these various experiences and discourses into communication with one another? AMM: Well, I don't set out with a mission, you know. But it seems to me there's a lot of drama there, there's a lot of pain and a lot of effort, and a lot of very, very good intentions, and a lot of anger. People are always terrified of losing something, terrified of change...

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.206
Threshold uncertainty score0.409

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0390.009
Scholarly communication0.0070.007
Open science0.0030.006
Research integrity0.0090.021
Insufficient payload (model declined to judge)0.0110.003

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 head0.045
GPT teacher head0.286
Teacher spread0.241 · 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 designQualitative
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

Citations4
Published2005
Admission routes1
Has abstractyes

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