Quo Vadis? LIS Postgraduate Education in the Philippines / Fernan R. Dizon, Karryl Kim Sagun and Ana Grace P. Alfiler
Bibliographic record
Abstract
The paper intends to shed light on the predicament faced by many Filipino librarians: the lack of local institutions offering Library and Information Science (LIS) post graduate degrees. The study also aims to look at Filipino librarians who have either completed and are currently pursuing LIS and non-LIS postgraduate education, either locally or abroad. The paper aims to illustrate the state of Philippine LIS postgraduate education by considering the number of librarians who pursued and are still pursuing postgraduate degrees, and identifying the universities they selected, locally and overseas. The data was gathered from responses to an online questionnaire posted on websites of local libraries as well as professional networks, and supported by phone interviews. Responses were further validated through electronic correspondences. The study yielded constructive information on the state of Library and Information Science postgraduate education. Most respondents pursued or are pursuing Education related postgraduate degrees within the country. Of the number of respondents, only a few pursued or are pursuing postgraduate education in Library and information Science in other countries like the United States of America, Canada, Japan and United Kingdom.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".