Inclusive Management in Public Administration: The Development of a Work-Centred Training Program
Bibliographic record
Abstract
In this article, we aim to understand how a training program can help managers promote inclusive management. We present the development and implementation of a work activity-centred training program for inclusive management in an institution of the Portuguese Public Administration. Using a mixed design-based research methodology, we brought 24 municipal managers into the development and implementation phases of the training program. We organized a focus group of managers to understand their experiences, constraints and training needs for the promotion of inclusive management in their work activity. Questions were put to them before, during and after program implementation. To promote inclusion actions in their work activity, we developed a 60-hour b-learning program. Our findings show the effectiveness of integrating work activity analysis and group reflection when co-creating the training program with participating managers to help them act in their work activity and meet the challenges of inclusive management. The managers reported they had improved their knowledge and resources for inclusive management in their work activity, particularly by thinking and creating together as a group. They valued the participatory and context-specific approach. We conclude that work activity-centred training programs can be key to enhancing the ability of managers to promote inclusive management. The participatory design fostered group learning, grounded in real work contexts, and helped the managers develop inclusion strategies. We provide insights into how inclusive management can be developed collectively, thereby showing the importance of collaboration between Academia and Public Institutions in the development of training programs.
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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 | 0.013 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".