Bibliographic record
Abstract
My roots are showing: as a girl from out around the bay who “idolized New York all out of proportion” – to quote Woody Allen’s Isaac in Manhattan – a sense of aspiration informs this project. Growing up in Newfoundland, I had two tenuous connections to New York: my mother voraciously read the american society bible “Town and Country” and my father travelled to New York twice in the 1960’s to visit his sisters, Mary and Bride, who as young women moved to Brooklyn from Chapel Arm, Newfoundland in the 1940’s. As a child ever envious that my aunts had unlimited access to such a cosmopolitan place, I was drawn to the idealistic notion of New York as a “magic city.” I idolized Mary, a fierce woman who was my template for what I imagined was the archetypal New Yorker: brash, quick-witted, uncompromising. As a child, I witnessed her throw the “chin flick” and it thrilled me. It was such a brazenly profane gesture from an old school God-fearing Catholic. And it was so New York! She remained close to my father until he died from complications due to Alzheimers in 2000. Now 95, and also with Alzheimers, she lives in an old age home in the same Newfoundland town where I drifted through the pre-fab hallways of my high school and plotted my escape to the magic city. But I would never have the cojones to move to New York like Mary and Bride, even though opportunities presented themselves to me. To this day, I remain an outsider: roaming the city with a camera, often strolling by Robert Frank’s house on the slim chance I might find him sitting outside – I hear it’s a habit of his. Frank, Garry Winogrand, Diane Arbus, Helen Levitt and Saul Leiter: I worship them in the same way I worshipped Aunt Mary. Their traces remain on the streets I walk: ghosts that whisper sweetly while I look forward and backward through my lens, caught in a temporal loop, searching for a city that I’m not sure exists, except in my head. New York looms large in the collective imagination and we all have our versions of it. This is mine.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.000 |
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.
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 teacher head, 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".