The Efficacy of Non-Anonymous Measures of Bullying
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Olweus checklist, along with most of the questionnaires commonly used in bullying research, is anonymous. The respondent is not required to put down his/her name. This has been accepted as the ‘best suited’ method of assessing bullying. However, this assumption has not been adequately tested, and there is contrary evidence that this method is more conducive to obtaining more truthful responses from the respondents. This study tested the issue of anonymity versus non-anonymity experimentally using a balanced design. A total of 562 elementary school children (grades 1-8) from two inner-city schools in Toronto took part in the study. The findings supported the hypotheses that the respondents did not differ in their report of the incidence of either bullying or victimization, regardless of whether they were required to identify themselves by writing down their names on the questionnaire forms. The advantages of using non-anonymous questionnaires in bullying and victimization research, as well as in intervention work in schools, are highlighted.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it