Bibliographic record
Abstract
Our investigation of axiology (study of values) allowed us to ascertain a hierarchy of values of pre-service education students concurrently enrolled in two degree programs. We discovered homogeneity which may be a consequence of the discipline (education) investigated and/or sampling, as 87 % were female, which reflected the female dominance of the current Ontario pre-service education program at our University, and males totalled only 13%. Our values are linked to our understanding of self-concept and character we believed. Our survey data were examined in terms of gender, year of study, and division of study. Homogeneity of values was revealed within ‘Terminal values ’ (end state of existence) as Family security was ranked highest. True friends was ranked second and Health ranked third; whereas Self-respect was ranked fourth and Freedom was fifth, leaving Equality sixth. For ‘Instrumental values ’ (modes of conduct) being Honest was ranked highest by the entire sample (n=319) and Responsible was second. Loving was ranked third and Helpful was ranked fourth highest. Loyal was ranked fifth and Ambitious was ranked sixth. Teaching is not neutral therefore values clarification for teachers is a matter of identity as we need to be aware of what values we possess and employ within our praxes.
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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.382 | 0.105 |
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".