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Record W4362510416 · doi:10.1353/rvt.2023.0015

The Texas Motel

2023· article· en· W4362510416 on OpenAlexaboutno aff
Jill Talbot

Bibliographic record

VenueRiver teeth · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicLatin American and Latino Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPopulationArt historyArchaeologyArtGeographyHistorySociologyDemography

Abstract

fetched live from OpenAlex

The Texas Motel Jill Talbot (bio) I don’t think I knew I was going until I pulled onto the highway. That was five miles back. It’s Saturday, mid-morning, mid-summer. I’m forty miles from Dallas on I-35 North. Up ahead, dark clouds drape the sky like a stage curtain. I wonder if I should turn back. When I hear the high guitar notes of Bob Welch’s Sentimental Lady, I turn up the volume. Sentimental gentle wind blowing through my life again. Ranches, acres of clear land, and solar energy fields line both sides of the highway, and traffic thins out as the lanes narrow from four to two. For years I’ve been wondering about the difference between memory and imagination. If there is a difference. I-35 begins in Laredo, Texas, on the Mexican border, and winds vertically through the middle of the country all the way to Duluth, Minnesota. In Texas, the highway cuts through San Antonio, Austin, and Dallas before it runs through the last town, Gainesville, population 16,441. 503.9 miles. The last Texas exit, 504, appears just before the bridge over the Red River, [End Page 51] the Texas/Oklahoma border. I live in Denton off Exit 465A, where the sign of a 7-Eleven rises above the overpass. I read somewhere that Bob Welch wrote Sentimental Lady in the Gorham Hotel in New York City in 1955. That hotel no longer exists. What happens to our stories when the rooms that once held them disappear? Traffic slows, merging to one lane. Ahead, a stout construction worker stands in the middle of the lane with a STOP sign while southbound traffic slowly passes. After a while, he turns his sign to SLOW. I wave as I pass him, thinking about a story I once heard when I lived in Utah for a few years about fifteen years ago. I don’t remember who told me. Maybe a colleague? Maybe a man sitting next to me at a bar? But here’s the story: A construction worker on I-15 outside of Park City stopped traffic. He stood in the middle of the highway, next to the first car waiting in the line. The driver rolled down his window and asked the worker how he was doing. The driver was Robert Redford. I also lived in northern New York for a while, in my late thirties, not far from the Canadian border. The landscape open, hushed. I’d go on drives along the quiet routes in search of abandoned buildings. There are plenty. There’s even a website: “Old Abandoned Buildings of Northern New York.” Collapsed barns, lonely silos, fences struggling to stand. Motor lodges strangled by brush, stone schoolhouses, stores with signs still intact. Pete’s Place. But it was the abandoned tavern on County Road 24 that fascinated me the most. Its faded sign, Turnpike on the stucco wall and above the entrance, wood cutouts of a mug, a martini glass, and a wine glass. A Harley Davidson sticker on the glass door. The place reminded me of a bar in Utah, one with a concrete floor and a sign behind the bar, Memberships $12 a year. A Utah law back then. I’d go afternoons after teaching class, arrive about the same time the salt-and-pepper-haired man did, the two of us setting down the day with the first pint. I don’t remember his name, but I remember his plaid shirts and weariness, his starched Wranglers and [End Page 52] stories, the ones about digging graves, waiting for the last mourner to leave before filling it. The toughest, he once told me, were the ones who stayed until he had stamped the raised earth with a shovel before heading to the excavator parked several feet away. He always felt bad leaving the mourner at the mound. What stories were told from the barstools inside the Turnpike? And how long ago did last call end with raised glasses of farewell before shadows spilled from the door and onto the gravel of the parking lot for the last time? The parking lot where I stood...

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.912
Threshold uncertainty score0.885

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.028
GPT teacher head0.322
Teacher spread0.293 · 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.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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