Bibliographic record
Abstract
As our country is celebrating 75 years of Independence, the yearlong celebration is termed as “Azadi ka Amrit Mahotsav.” It also shows how we have progressed over the years towards an “atma nirbhar bharat” (self – reliant India), which has proved itself in the field of commerce, industry and other infrastructural areas including education. In today’s challenging scenario especially after the re-opening of school, colleges, institution after the Covid lockdown for nearly 2 years, all of us are still finding ways and means to cope and understand each other’s behaviour and expectations. Realizing the importance of values in our life, it is crucial to inculcate empathy, tolerance, inclusion and acceptance in our everyday lives to be a healthy and successful individual. For inculcating values, we must follow the UGC document of Mulya Pravah focusing on the righteousness, love, compassion, peace, and non-violence of any academic leader. While producing graduates’ universities must focus on not only making them successful but also on what moral character they bear? The role of students must be useful to the societal fraternity and even to their own institution and nation-building. We must build patience and tolerance among them. Students must be trained to behave and formulate decision-making power in extreme situations. They must be taught the qualities of perseverance and persistence, kindness, the value of service, and mental strength along with physical growth. Engendering morality among academicians cum students provides the basis for honesty, loyalty and social responsibility needs to be implemented in their everyday lives. This morality then impacts our society and nation through our respective actions. In current scenarios, where we are dealing with the moral, cultural and mental crisis it is necessary to ensure the mental and physical well-being of academic community for their holistic development
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".