Bibliographic record
Abstract
MY MOTHER'S ENGLISH ACCENT always set her slightly apart from us. There was nothing foreign in Dad's Boston drawl. He said hosses and we said horses, but we were Costellos, even if Ohio born. When we were little, squabbling over a game or a toy, we'd call Mom! (never Mum) to referee, and she'd answer back dismissively from the next room: Ran a-way with a sol-dier, knowing we would settle it on our own. Just one of her funny expressions, we thought, that nobody else's mother used, like Let's gather up the bits and bobs or Let's spend a penny. When I try now to imagine Marjorie Embrough on her way to becoming Marjorie Costello, I start where she got stuck: Goose Bay, Labrador, March 15, 1946. Transatlantic passenger flights were rare in those days. Her plane, a cargo flight that took a few passengers, was three days delayed in London because of weather. So she was already late for her wedding. And then they had stopped in Goose Bay to refuel, but a storm was again keeping them grounded. I imagine her looking out the hangar window across the long gray runways flanked by narrow pines and bleak hills. Nearby Newfoundland, she surely knew, was my father's birthplace, though the family of six had left Pouch Cove and moved to Boston's North Shore when he was small. Gazing across this frozen limbo, she must have wondered just what sort of life they'd led there. Goose Bay was the home of fish, seals, puffins, and a few thousand Allied air force staff and support. Was Pouch Cove much different? With so little of interest in this field of vision, and so many hours of waiting, she could finally look back on what brought her to this odd junction. She had just turned nineteen. The war had been her whole adolescence. The future was hard to picture. My parents met at a dance (that much is proverbial) in her hometown of Stafford, England, when she was seventeen and he was thirty-one. The dance had been organized for the American servicemen stationed nearby in preparation for the Invasion. To me it's only a storyboard: Mature, uniformed officer with a melancholy past, chaperoning his unit, spots lovely young redhead, and a three-week courtship begins. Promises and tearful farewells before shipping out for France, a year of letters from the front, a brief, passionate furlough, an engagement, another long separation, and now he has sent for her. Stories pull us along with their inevitable plots. But for her there must have been some doubt and ambivalence even at this late hour. She'd passed the Cambridge entrance exams. She might be reading in English or history at Girton or Newnham now, in one of those old stone libraries. But study had seemed so irrelevant in 1944. Everything at home was so shrunken, pinched, and dreary. She'd wanted to do something, more than write letters to the front. The nurse training program had put up signs everywhere. The hospitals were desperately understaffed, even as the war ended. So instead of Cambridge after graduation, she'd signed up for nurse training at Westminster Hospital. She'd found out soon enough just how unsuited she was for the caring profession. She was no Florence Nightingale. And it wasn't as if she were free to roam around the unlit streets of London till all hours. They kept strict parietals at Westminster. And the robot bombs were still dropping in 1945. Not that there was much left of London anyway. Everybody seemed to be living underground. During the war whole communities had moved to the shelters and subways, setting up bunks, canteens, telephones, triage stations. Now that was over with, at least. Everybody was coming up for air, filling the cinemas and theaters. But there was little of the pageantry of London life, the extravagant shops and nightclubs, the elegant gowns and top hats that she had fantasized about in her boring Midlands youth. Of course she knew that many of these Londoners had been living cramped, dingy lives even before they entered the shelters. …
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.380 | 0.163 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".