Using simulation to explore reciprocal help seeking in a lifelong learning context
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
In one form or another, every institution participates in business process management practices to constantly improve the delivery of their services. But, as the processes change, so must the employees who have to adapt their knowledge to the changed circumstances by learning from their peers. But whom should an employee ask for help? We propose using simulation as a means of exploring the interactions between help seeking and help giving, to explore the importance of reciprocity, and to understand the impact of incorporating a reciprocal recommender system. We describe SimGrad, a process-based design framework for a simulated graduate school (our 'institution'), as a focused context for studying LLL issues. We use agent-based simulation to model lifelong learners, and discrete event simulation to model their interactions in the help seeking process. While the simulation has not been implemented, the promise of this approach is illustrated through a scenario and example.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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