The Future Gap: Exploring a Critical Reflective Stakeholder Approach
Bibliographic record
Abstract
The focus of this paper is a participatory design process that is used as a means to enable multiple stakeholders' collaboration in discussing strategies, designs and solutions of a conceptual future factory. The reason for this study is the Swedish industrial sector's difficulty in attracting women and young people. The design process can adapt to various complexities, building on the creative and innovative ability of collaborating people. In the present study, young people participated in explorations of images and perceptions of the current industrial sector and in an inquiry into the needs and preferences of a future factory. This activity resulted in two future scenarios: utopia, a positive future vision, and dystopia, a pessimistic outlook. These scenarios subsequently were used as means for critical reflection with multiple industrial sector stakeholders, exploring the future gap as the discrepancy between the images, perceptions and understanding held by internal stakeholders compared to external stakeholders. In this paper, we propose scenario-based design as one approach to multi-stakeholder activities, both for understanding various stakeholder needs and preferences and for critical reflection on future strategies and visions with a diversity of stakeholders. We believe there is a need for a transformation in the way in which organizations involve and connect to stakeholders.
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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 | 0.080 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.017 | 0.038 |
| Scholarly communication | 0.018 | 0.028 |
| Open science | 0.005 | 0.017 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".