Bibliographic record
Abstract
People’s actions are governed by their values, beliefs, perspectives, and world views. There is so much diversity that everyone has or creates their own moral standards, principles, and values, making social cohesion difficult. We come to a dead-end when we evaluate different moral standards and value systems from the perspective of relativity and absoluteness. People acquire values first in the family and then at school. Therefore, teachers play a crucial role in helping students adopt values and moral standards. This study investigated teachers’ views on values (especially lost values). This study adopted a qualitative research design (phenomenology). Data were collected using a semi-structured interview questionnaire developed by the researcher. The questionnaire consisted of six questions. The study sought answers to the following questions: What do teachers think about values and values education? What values do teachers think we have lost in society? Why do teachers think we have lost values in society? and How do teachers think we can get back the lost values? Participants viewed values as moral principles. They regarded values education as the type of education required for society to live in a healthy, harmonious, and peaceful way. They thought that we had lost the values of honesty, understanding, respect, etc. They believed that we had lost those values because of social media, changes in the institution of family, etc. They suggested that we provide students with values education courses and encourage school-family collaboration to get back the lost values.
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 | 0.013 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.030 | 0.055 |
| Scholarly communication | 0.023 | 0.023 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.005 | 0.016 |
| 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".