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
Purpose The purpose of this article is to share with readers details of this consortium's multicultural virtual teaming project implementation and the lessons learned from experiences of the participating students and professors. Design/methodology/approach To establish a preliminary relationship, virtual student teams exchange e‐mail messages with team mates at participating universities that provide introductions for each member of the team. Each team member uses these individual introductions to write a brief paper that introduces all team mates. Next, the students virtually interview one another to obtain answers to culture‐specific questions for each culture that is represented on the team. In some courses, this information is analysed using Hofstede's four dimensions of culture: power distance, individualism versus collectivism, uncertainty avoidance, and masculinity versus femininity. Findings Based on participants' experiences in these virtual teaming projects, the following recommendations are presented: emphasise relationship building; solicit widespread input for planning; and balance individual control with shared objectives. Originality/value These cultural virtual teaming projects proved to be valuable learning experiences for both the students and faculty who were involved.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.005 |
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