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Record W7069576967

Morris, Paula

2005· article· en· W7069576967 on OpenAlexaboutno aff

Bibliographic record

VenueDigitalResearch@Fordham (Fordham University) · 2005
Typearticle
Languageen
FieldComputer Science
TopicComputational Physics and Python Applications
Canadian institutionsnot available
Fundersnot available
KeywordsBoroughDanceBoarding schoolQuarter (Canadian coin)ClubLuck
DOInot available

Abstract

fetched live from OpenAlex

Paula Morris’ earliest memories of the Bronx are of Ritter Place. It was majority African American and had a great sense of community. Her father was initially a police officer, but later in life became a photographer. She was always aware that her mother, Maxine Sullivan, was a famous musician. Her mother’s fame, however, did not affect her upbringing. She still had to live by the same rules as everyone else she knew.\nShe attended P.S 54 for elementary school. The sense of community she experienced on her block continued at the school. Parents were always involved with their children. The school was multi-racial and she had friends from all different races and who lived on different blocks. The school did have a few African American teachers; for example her math and kindergarten teachers. During this time, her mother was still performing in Manhattan and many musicians were still coming to their house to have jam sessions. Early in her grade school career, she attended at Dance school in her neighborhood. She was best at acrobatics. In the third grade, she was sent to boarding school for the year at Onteora Central School. That year her mother was doing a lot of traveling and did not want to leave Paula at home or with baby sitters.\nShe attended junior high at P.S 40. Here, she began playing the Cello, which she was allowed to bring home on weekends to practice. She was talented enough to be in the borough wide orchestra for two years. She was also in their marching band. Through her involvement with the Bronx orchestra, she met a lot of future famous musicians, like Jimmy Owens. When she was PS 40, her mother began telling her she had to think about a career. She thought about something in the medical profession and started volunteering at Lincoln Hospital.\nAfter, P.S 40, she attended Evander Childs High School. Her academic experience here was more challenging and she was a cheerleader. The year she started at Evander, was the year that there was a big fight between Evander students and students from DeWitt Clinton High School after a football game. After high school, she began working at Equitable Life Insurance Society as a messenger. However, shortly thereafter she began nursing school at King’s County Hospital Center in Brooklyn. It was a three year residential program. When she graduated, she first worked as the head nurse of open-heart surgery at Einstein Hospital. Though this was a very stressful job, she really enjoyed it.\nWhen she finished the program she returned to the Bronx. At the time, other neighborhoods were being hit by the drug problem. Fortunately, Ritter Place was never touched. In 1969 she got married and moved to Riverdale. However, through working with her mother, she would frequently come down to Prospect Avenue and see the destruction caused by the fires.\nIn 1975, her mother founded The House That Jazz Built. This was a program to teach children about music and Jazz. Paula served as the fiscal officer. Many people on the board of directors were former musicians. The parents and children participating were very enthusiastic and involved. They would frequently perform at different venues around the Bronx as a means of fundraising. One of the biggest problems they encountered was the low literacy rate of the students entering the program. Because of this, they began working to address the literacy problem as well.

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)0.003
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.741
Threshold uncertainty score0.868

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.2590.102

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 head0.018
GPT teacher head0.241
Teacher spread0.223 · 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 designNot applicable
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
Published2005
Admission routes1
Has abstractyes

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