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Record W2052425312 · doi:10.1353/rcr.0.0059

Just Here for Littering

2010· article· en· W2052425312 on OpenAlexaboutno aff
Erin Wisti

Bibliographic record

VenueRed cedar review · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicArchitecture, Design, and Social History
Canadian institutionsnot available
Fundersnot available
KeywordsConversationFace (sociological concept)White (mutation)Visual artsArtArt historyReading (process)AestheticsHistorySociologyLawPhilosophyCommunicationLinguisticsPolitical scienceChemistry

Abstract

fetched live from OpenAlex

Just Here for Littering Erin Wisti (bio) I wanted to say no. I hated Starbucks. The entire place smelled like it was wrapped in plastic, sealing the customers inside a shell of coffee beans and artificial flavoring. It was free of any conversation that didn't involve the ordering of frappuccinos or mocha lattes. Everyone was plugged into iPods or laptops as they roasted in the far too bright overhead lighting, clattering away on their keyboards and iPhones. Plus, you couldn't use the bathroom without buying something. This always seemed unfriendly. Generally, I tried to avoid the place, but on that day I could not have said no. My mother taught me sick people should always get whatever they want. I had no choice but to take him. He sat across from me at our table, reading a copy of Watchmen. The glossy, yellow and black cover reflected the fluorescent lighting onto his glasses. I called them his "Henry Kissinger glasses" because large frames and thick rims resting on a wrinkled, fifty-one year old nose are always reminiscent of Kissinger. My father's face, square-like with a pronounced nose and untraceable jaw line, also reminded me of Nixon's ancient secretary of state. I studied his face as he read. My choice of book for the day—Fried Green Tomatoes at the Whistle Stop Café—had proved uninspiring and it was clear no conversation was going to take place on our outing. A small beam of white light trickled down the golden frames and swept across the lenses as he turned the book's page. We were at a Barnes and Noble that housed a Starbucks in its center, a common feature of bookstores in the Midwest. We were away in Rochester, Minnesota, the land of romantic imagery. Bright green trees filled with fresh purple lilacs lined the Zumbro River, where slender black and tan Canadian geese floated alongside canoes. These canoes were driven by happy suburban families who looked like they were posing for ads in Eddie Bauer or JC [End Page 68] Penney's, donning new spring clothing in coordinated shades of pastels. I walked down the asphalt path by this river many times that week, puttering behind my father. In his light gray sweat pants which sagged at his crotch, he marched in front of me, taking long, sweeping strides while periodically checking his heart rate. He wore expensive, Nike-brand running shoes, one of the many new toys we bought for him when we found out he was sick. He was quite pleased with how they improved his pace. I, however, wore cheap plastic flip-flops from CVS and waddled behind him and took pictures. I photographed the lilacs and the geese and the suburbanites, the whole time wondering if taking pictures was morbid considering the nature of my visit. I was visiting because he was sick and because he was sick, I had to take him to Starbucks. His phone rang. It had been ringing all morning, even before we left Hope Lodge to get coffee. I wasn't following the conversation closely. It was lawyer talk, a phenomenon I had been familiar with since childhood. He would waltz through the hallway at night in his tattered red robe, barking legal terms into our cordless phone while making his way through a pack of Marlboros. He was always talking to Sammy, his brother and business partner. Sammy relied on my father's help with his cases, which I knew never to ask questions about. I knew most of them were illegal to answer. That day, it was something about a bowling alley, something his brother couldn't handle alone and so, even though he was sick, he took the calls from Sammy's clients. "I gotta go, Chuck," he said, "No. I really gotta go. I'm with my daughter." He sputtered a few rushed goodbyes and then snapped his phone shut and slipped it into the large, floppy pockets of his sweatpants. "Jesus," he muttered. "What?" I asked. "Listen," he said, "Don't ever be a lawyer. Being a lawyer means people expect you to solve all their problems all the...

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.446
Threshold uncertainty score0.790

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0040.001
Scholarly communication0.0050.005
Open science0.0010.006
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.4460.354

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 head0.065
GPT teacher head0.282
Teacher spread0.217 · 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.

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

Citations0
Published2010
Admission routes1
Has abstractyes

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