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Record W4312731122 · doi:10.1353/rvt.2022.0020

On the Hairline Fringe

2022· article· en· W4312731122 on OpenAlexaboutno aff
Ana Maria Spagna

Bibliographic record

VenueRiver teeth · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicRace, History, and American Society
Canadian institutionsnot available
Fundersnot available
KeywordsBeaverArchaeologyGeographyHistoryGeology

Abstract

fetched live from OpenAlex

On the Hairline Fringe Ana Maria Spagna (bio) A cardinal sits on the fence in the snow framed by Christmas lights. I’m riding a bike trainer on a sunporch built for tubercular patients a century ago, trying to take a photo with my phone, but the cardinal is obscured by window screens, and this North Country day is gray as cement. The cardinal cranes his beak skyward, casting about for what? A mate? A better feeder? I pedal harder, wave my arms to a headphone beat, sip water, check headlines on the tiny screen, squinting without specs, catching the gist of the news: tenuous, steady, tenuous, steady. I am fifty-three years old, 3,000 miles from home, out of place, out of sorts—by choice, true, and anyway, who isn’t these days?—and unspeakably grateful, mid-pandemic, to be away from the center of attention, geographically and culturally, on the fringe again. The North Country, broadly defined, covers the northeast corner of New York State from Lake Ontario to Lake Champlain, from the Adirondack Mountains to Canada. This sliver where I’ve landed, which might be called the North-North Country, fills the margin between the St. Lawrence River—the Canadian border—and the Adirondack foothills. One of my students called it “the hairline” of New York. Six hours east of Buffalo, six hours north of the city. Beaver abound in the woods. Sandstone spires grace every third corner church. The Grasse River, once industrialized, ambles [End Page 49] through town past reeds and over rocks beneath white pine limbs stretched impossibly straight. In winter, tannic riffles freeze the color of root beer froth. Drive to the mountains and you pass rolling hills of fallow crops and smaller homes in disrepair with green board exposed and torn flashing and all manner of flags: Blue Lives Matter, Don’t Tread on Me, Trump, Trump, Trump. Back in the village, big old houses line tidy neighborhoods with dormers and porches and paint-peeled flourishes of railing or brace. And these elaborate sleeping porches left from a forgotten plague. One day when the temperature hovered in the teens, I stopped at a mini mart, stepped to the register, and stood behind a man whose pant cuffs flapped on the floor. He wore a mask, thank God, and a ball cap with a lady bug on the brim. “It’s spring for this lady. Soon for all of us,” he said. He was the only real-live human I spoke to all day. Sometimes I’d picture the tubercular patients in Adirondack chairs, their faces to the sun, blankets in their laps, possibly a cat. Can we agree those chairs are awkward? Ridiculously low and deep. Once you sit, you can never rise gracefully. Nevertheless they’re ubiquitous here and elsewhere, on suburban decks and lakeside lawns. These large screened-in porches, on the other hand, had a short day in the proverbial sun. In the early twentieth century, “cure-inspired architecture” went from stigmatized to stylish to useless-once-air-conditioning-came-on-the-scene. The see-through appendages sat empty, at least in winter, oversized voids. Each day at five, I’d take a beer and a coat out onto mine to listen to the abhorrent news on the radio and drag a string around for the cat, Maybelle, who came with the house. I moved to this hairline place from another where, for years, I sat face-to-screen in a cabin alone and taught online in order to live in a place close to trees and dirt. What I mean is I’d done enough forest bathing to prune my skin. What I mean is I was ready for a change. What I also mean is that I’d been well trained for a pandemic, able to endure or embrace disconnection, accustomed to the stuck-in-between feeling like floating, like the fever dreams of youth or the long days in early adulthood when you’d take a car to be repaired and have nothing to do but wait to hear if it could be fixed and what it would cost. I landed alone, for three months...

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.590
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.268
Teacher spread0.249 · 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
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

Citations0
Published2022
Admission routes1
Has abstractyes

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