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Record W2905439396 · doi:10.2979/chiricu.3.1.16

In Washington Heights

2018· article· en· W2905439396 on OpenAlexaboutno aff
Luis G. Valerio

Bibliographic record

VenueChiricú Journal Latina/o Literatures Arts and Cultures · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsApartmentBrotherDoorsLiving roomQuarter (Canadian coin)HistoryWifeArt historyVisual artsSociologyArtLawArchaeologyEngineeringPolitical scienceAnthropology

Abstract

fetched live from OpenAlex

In Washington Heights Luis Guzmán Valerio (bio) The Washington Heights neighborhood has always held a certain symbolic value in my life. As a child, my mother would bring me and my little brother to visit relatives in the neighborhood. None of them stayed. Tía Albertina and her family moved to Kissimmee and tío Toño and his family moved back to the Dominican Republic. As an adult, my father committed suicide in his apartment on 181st Street. I was in Puerto Rico at the time. Washington Heights is a place that has beckoned me, pushed me away, drawn me in, and made me want to get the fuck away. My earliest memories are of visiting my great-grandfather in the neighborhood. I might have been three years old. That's how old I was when I was first brought over from the DR. I remember my great-grandfather lived in a huge apartment with a separate living room, dining room, and kitchen. The rooms seemed endless to me as a three-year-old. A set of French double doors with divided glass panes separated the living room from the dining room. The first time I saw those double doors open up made an awesome impression on me. I had never seen anything like it. I remember looking out a window from that apartment and seeing sailboats on the Hudson. The apartment could have been on Riverside Drive. On a visit to Santiago de los Caballeros in my twenties, I found out from my great-grandfather that he had started coming to New York in the 1950s, during the Trujillo dictatorship. How he was one of the lucky ones able to get a visa at that time, I do not know. What I do know is that the right to migrate to the United States was passed on from one relative to another, like an inheritance. My great-grandfather lived with several great-aunts and second cousins in that huge Washington Heights apartment. On one occasion, when I was very young, my mother left me overnight with my cousins, aunts, and uncles so that they could babysit me. My cousins introduced me to eating Frosted Flakes [End Page 206] with Coca-Cola. We watched a movie on TV where some monster grew in a person's stomach. The stomach exploded and the monster came out. After eating the Frosted Flakes with the Coca-Cola, I thought the bubbles and the gas in my stomach were going to make it explode. I had nightmares that night of a monster exploding out of my stomach. When I visited, I appreciated all the attention I received from my extended family. My mother didn't recall those days fondly though. Later on in life, she told me she only had one pair of jeans when she first came to New York y que en el invierno se moría de frío. That first winter in New York she wore those jeans until they wore out. You see, coming to New York for my mother was not a luxury. My grandfather kicked my mother out of the house when she was sixteen because she was pregnant. The nuns also kicked her out of Catholic school. She went to live with her tía Masa and got a job en la Zona Franca sewing brand-name American clothing for slave wages. There was quite a narrow future for a seventeen-year-old mother in the Dominican Republic. Tía Masa arranged for my mother to marry her cousin Julito so that she could get a visa ASAP and come to Nueva York, where opportunities abound. My mother had to get away from the stigma of being a teenage mother, getting kicked out her home, and kicked out of Catholic school. If only it were that easy. In New York, her aunts and cousins were harsh and unforgiving, passive aggressive. How dare she not protect her most prized possession like they had. My father didn't have it easy either. The story goes that my grandfather chased him around town with a gun and wanted to kill him. You see, that's the way...

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.639
Threshold uncertainty score0.514

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.6390.374

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 head0.325
Teacher spread0.306 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
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
Published2018
Admission routes1
Has abstractyes

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