Bibliographic record
Abstract
Interviewers: Brian Purnell and Oghentoja Okoh\nInterviewee: Veronica Buapin\nDate Of Interview: October 5, 2004\nSummarized By Eddie Mikus\nVeronica Buapim is a Bronx resident who was born to Ghanaian immigrant families. Her life story depicts the experiences of a Ghanaian growing up in New York City as well as the evolution of the city’s community.\nBuapim was born on March 10, 1983, at Our Lady of Mercy Hospital. Her parents came from different Ghanaian tribes and had 9 other children (seven of which were full siblings to Buapim). Buapim grew up in a residence called Academy Gardens, which was across the street from the Soundview projects. As a child, her father attempted to maintain some Ghanaian cultural practices within the family home; however, her mother focused more on religion than on culture and Buapim never learned how to speak Twi. During her high school days, Buapim made friends with a few other Ghanaian students and took part in after-school activities such as student government and tennis.\nDuring her childhood, Buapim witnessed several demographic and lifestyle changes that occurred in the Bronx. For example, she said that in the 1980’s there were more blacks in the building where she lived, while the present population is more Hispanic. Furthermore, Buapim said that the building had a vibrant sense of community and a well-attended summer camp prior to a takeover by new management when Buapim was 12 years old. She also noticed increases in street violence and use of marijuana in the years after the new management took over—even relating an anecdote about how her brother was hurt in the ankle due to a gunshot.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.166 | 0.021 |
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".