A Serious Game for Evaluating the Competencies of Environmental Consultants
Bibliographic record
Abstract
Having a competent workforce is one of the key elements that enable organizations to improve their global performance Thus, it is important for an organization to manage the competencies of its staff in the best possible way. In this paper, we present a serious game named EnviRun', that evaluates the acquired competencies of environmental consultants _ The environmental consultant advises and assists industries on projects related to the environment and sustainable development_ Indeed, Competency evaluation allows the organizations to define the potential of existing competencies and to specify competencies that need to be improved. To this end, the first step was competency identification. Indeed, we developed a competency framework that includes competencies required by an environmental consultant. Thereafter, the game elements were designed. To evaluate the environmental consultants' competencies, an approach based on the interval-valued 2-tuple linguistic representation model has been proposed, this approach is more flexible when dealing with qualitative information.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".