A Comparative Study of the Publication Output of Librarians and Academics in Universities in the South-South Zone of Nigeria
Bibliographic record
Abstract
This study is aimed at examining the publication output differences between librarians and academics at Niger Delta University and Delta State University in Nigeria. The study employed a comparative method. The study comprises focus groups made up of thirty librarians and forty academics (teaching staff) from Niger Delta University (NDU), Amassoma, Bayelsa State; and Delta State University (Delsu), Abraka, Delta State. Questionnaires and interviews were used for data collection. The data obtained from the questionnaires were analysed using simple percentage to answer the research questions and a chi-squared statistical tool of significance to test the formulated hypotheses. The study revealed the following: that librarians and academics in the two universities published equally; that high qualifications influence the publication output of librarians and academics; and that long daily working hours, heavy workload, a limited number of local journals, and high publication charges are some of the major problems militating against the publication output of librarians and academics in Nigeria. The study will stimulate librarians, despite the obstacles militating against their publication efforts, to see the need to publish like their lecturing counterparts in order to meet promotion requirements. The findings of this study should move university authorities in Nigeria to set aside time (hours or days) for research activities for all academic staff as directed by the National University Commission (NUC) in Nigeria.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".