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Record W4253268537 · doi:10.1353/tyr.2014.0056

SUMMER LOSSES

2014· article· en· W4253268537 on OpenAlexaboutno aff
PAULA FOX

Bibliographic record

VenueThe Yale Review · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Studies and Interdisciplinary Research
Canadian institutionsnot available
Fundersnot available
KeywordsWifeBayCapeShoreArtAncient historyHistoryArchaeologyOceanographyLawGeologyPolitical science

Abstract

fetched live from OpenAlex

6 4 Y S U M M E R L O S S E S P A U L A F O X Half a century ago I and my husband of those years, Richard, built a house on the ocean shore of Cape Cod, a few miles from the town of Wellfleet. A quarter century before that, in the 1920s, my father, Paul, and Elsie, his Spanish wife, had bought a cottage on Commercial Street in Provincetown, a few minutes’ walk from the theater of a small acting group, the Provincetown Players, to which my father belonged. Elsie was my mother. I never lived with them except for three days when I was three; and then when I was fifteen, after they were divorced, for three weeks with my father on a Canadian island in the Atlantic Ocean. One late autumn day while they were in New York staying in a hotel, an arsonist in Provincetown burned their small cottage to the ground. On a summer’s afternoon during my father’s only visit to the Cape and to see us in the two years that Richard and I lived there, I drove Daddy to Provincetown. As we moved slowly along the carchoked street, passing a long gray wharf that seemed to be stumbling out over the bay waters, my father said, ‘‘I remember Eugene O’Neill standing out there, leaning against a post, wearing an old blue sweater, smoking a cigarette.’’ 6 5 R A moment later he pointed out where a bootlegger of those Prohibition days had lived in a small house on machine-gunprotected land. He spoke of seeing from his bedroom window Isadora Duncan’s young brother striding along Commercial Street dressed in a white toga and wearing sandals on his long narrow feet. ‘‘Extreme,’’ he said, ‘‘even for those wild days.’’ We spoke of the death of Susan, a young actress in the theater group. As she lay dying of an illness he didn’t name, in a rented room of the large yellow-painted house we were then passing, her last request had been to be cremated and have her ashes flung into the sea from a blu√ a few miles from Provincetown. When she died, after a short ceremony following the cremation, two of her women friends from the theater group drove to the blu√. They parked a few yards from the edge. There was a bald spot on the sandy earth where people stood to look out to sea or to stare down at the narrow beach far below with its snake-thin streams of dark water that washed about large gray boulders. The women didn’t speak as the one who drove got out of the car and the other reached over the back of the seat to pick up the urn. The two, still not speaking, stood on the cli√’s edge. Then one said ‘‘Now!’’ and the other opened the urn after a moment’s di≈culty , and holding it at arm’s length began to shake it. A sudden gust of wind blew up the side of the cli√ and struck, scattering Susan’s ashes in their faces. I drove the few miles to Wellfleet one late weekday morning to pick up a friend who worked in a real estate o≈ce. I was to drive her to Provincetown – I don’t remember why – and on our way we passed one of the freshwater ponds well known to local people and regular summer visitors. ‘‘That’s Grandfather’s pond,’’ my passenger remarked as we passed it. ‘‘Is that how it’s called, its name?’’ I asked. ‘‘No,’’ she replied. ‘‘It belonged to my grandfather, Admiral Nimitz.’’ The populations of Wellfleet, Truro, and Provincetown changed from year to year, constantly. Summer people mingled with local people for the two or three months of each season. Those with two 6 6 F O X Y or three weeks o√ from their jobs squeezed into narrow rooms of motels from whose stale air they would escape each day, even into falling rain, for the glory of the seawater – then return to the suburbs and big cities where...

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.416
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.002

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 head0.140
GPT teacher head0.344
Teacher spread0.204 · 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; both teacher heads agree on what is shown here.

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
Published2014
Admission routes1
Has abstractyes

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