Bibliographic record
Abstract
The alumni tracer study investigated the profile, current employment conditions, and place of work of USPian alumni in 20 higher education programs including only those who major in English, Political Science, Psychology, Music, Social Work, Elementary Education, Secondary Education, Pharmacy, Commerce, Accountancy, Civil Engineering, Mechanical Engineering, Electronics & Communications Engineering, Geodetic Engineering, Electrical Engineering, Architecture, Computer Science, Information Technology, Nursing, and Law from Classes 2001 to 2010. The descriptive research design is utilized in tracing 2668 USPian alumni with a success rate of 12.7% or 340 actual alumni response. Based on the general findings of the study, the majority of the USPian alumni are working in line with the degree they earned at the University and were mostly Philippine-based. The minority are spread out to 15 foreign countries: Australia, Bahrain, Canada, Japan, Jeddah, KSA, Netherlands, New Zealand, Norway, Oman, Qatar, Singapore, UAE, UK, and the USA. Recommendations to improve alumni profiling, eliminate current conditions of unemployment, embark on industry-perspective alumni research and other topics for future researches are recommended.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".