NAFTA Students'Whistle-blowing Perceptions: A Case of Sexual Harassme
Bibliographic record
Abstract
Whistle-blowing mechanisms in the U.S. have gained more prominence as an element of legal compliance and antifraud programs. Sexual harassment is a significant business risk in \nterms of financial costs and the loss of reputation. lt is important for corporations to develop sexual harassment policies and to provide mechanisms for employees toreport sexual harassment behaviors to upper level management. This paper reports on business students' responses to a possible Sexual Harassment scenario from Arthur Andersen's Business Ethics Program and the actions that the characters in the video should take in terms of whistle-blowing. l fall 2004,78 students from two U.S. universities and one Mexican and one Canadian university participated in \nthe prolect as part of the NAFIA Challenges of Accounting and Buslness Sysfems Granf funded by the United States Department of Education Fund for the lmprovement of PostSecondary \nEducation (FIPSE), Human Resources Develópment Canada (HRDC), and Mexico's Secretaría de Educación Pública (SEP). Students from the three NAFTA countries were shown the vignette and asked to respond to a pre-questionnaire concerning the characters' behaviors and possible actions. The students were then asked to discuss the situation and write a reoort from the points of view of the three characters in the vigneite and also to find a copy of an organizations' sexual harassment policy from the Internet. At the end of the project the students responded to a post \nquestionnaire. The students were asked to consider whether the characters should report the possible harasser totheir supervisor, and thus engage in whistle-blowing behavior. Hypotheses are formulated for the three NAFTA'countries based on Hofstede's cultural dimensions and comparisons are made based on overall responses to the pre-and posfquestionnaire. There were significant differences, but in some cases not in the direction expected. Gender differences are also explored, but there were few significant differences. The authors are working under the \nNAFTA Challenges of Accounting and Busrness Sysferns Grant from the United States Department of Education Fund for the lmprovement of PostSecondary Education (FIPSE), Human \nResources Development Canada (HRDC), and Mexico's Secretaría de Educación Pública (SEP)
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.006 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| 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 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".