Validación de la prueba de escala de altruismo Self-report en estudiantes universitarios colombianos
Bibliographic record
Abstract
Objective: to establish whether the Canadian selfreport altruism scale Questionnaire is a reliable estimate for altruistic behavior in young Colombian university students. Methodology: the self-report altruism scale test was adapted and applied. 327 university students between 18 and 25 years from five independent cohorts participated in this study. Participants should note, in 20 items, the frequency (never, once, more than once, often or very often) with which they performed altruistic behavior. The method of this study followed the protocol of the World Health Organization for these cases. There was also a correlation analysis between the score of the questionnaire and the evaluation that some close friends of each participant made in relation to the altruistic tendency of the latter. Results : cronbach's alpha, bipartition analysis and comparison of these data with those reported in other countries show that the instrument is highly reliable. The selfreport altruism scale questionnaire is a useful tool to estimate the altruistic behavior of Colombian university students. Conclusions: the relevance of developing tools to assess prosocial behavior in the country is discussed and clarified. Expanding the age range and applying the questionnaire to non-university populations, will strengthen the development of the instrument.
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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".