Mai Nguyen, They Killed Our Country
Bibliographic record
Abstract
[profile bio] Mai Nguyen is a survivor of the American War in Vietnam with a unique perspective and a compelling story. Ms. Nguyen was born in 1957 and lived in Saigon, Vietnam until her escape in 1980. Ms. Nguyen and her family were South Vietnamese who witnessed the American military influence and considered them a good symbol to keep Vietnam intact from communism. After the fall of Saigon in 1975, Ms. Nguyen witnessed first hand the oppression brought by communism and the elimination of freedom. In 1980 she decided to escape with her baby boy to international waters. However, in her escape, she became part of what is called the "boat people" and she encountered a hard and arduous journey. Pirates held up her boat various times, people around her were mugged, raped, and beaten—fortunately her strong will and faith in God saved her. Upon docking she arrived in Thailand as a refugee. Later, she moved to Canada, opened two successful restaurants and has been an anti-communist activist for the Vietnamese Community ever since. Ms. Nguyen later immigrated to the United States and her transition was also not easy. However, after confronting hardships in America she finally found peace. Mai Nguyen now resides in a beautiful neighborhood in Anaheim, California having raised two successful children. [profiler bio] Joseph Donaway is a senior majoring in psychology. Juan Cueto is a senior majoring in business administration. Diego Ramirez is a senior in the Viterbi School of Engineering.
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 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.267 | 0.062 |
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".