Repercussion of Using Internet Sources: Dilemma for Research Communities
Bibliographic record
Abstract
Objectives – Consultation of internet sources for educational and research purposes is the new normal. As a result of information communication technology, information creation and access are more convenient. The current study was carried out to investigate the proportion of use of internet sources for research purposes by research scholars of three central universities of North East India, namely Tezpur University, Mizoram University, and Rajiv Gandhi University. Methods – The researchers collected data from 123 respondents through an online questionnaire that was distributed through different social media platforms. The study was conducted among Research Scholars (PhD and M.Phil) of Mizoram University, Rajiv Gandhi University, and Tezpur University. Results – The research results show that research communities are moving toward digital platforms for searching and consulting their required resources. Most of the respondents consult internet sources for writing their research reports, but they do not format the references properly. Some research scholars do not follow any referencing style for citing web documents, and respondents do not have much awareness about the differences between URLs and DOIs. Research communities also face problems due to the inaccessibility of online documents cited by former researchers. Conclusion – Since most of the respondents are not familiar with the use of web archives, the current study suggests that higher education institutions should arrange awareness programs on the use of web archives. Research communities should follow the proper referencing formats to acknowledge others’ works. Publishers should mandate a citation style for authors and verify the accuracy of the references before publishing articles or other works.
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 | 0.158 | 0.320 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.030 | 0.040 |
| Scholarly communication | 0.026 | 0.032 |
| Open science | 0.006 | 0.027 |
| Research integrity | 0.012 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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".