Latour’s Discernment Tools in Action: Exploring and Solving Complex Social Problems Through Participatory Methods
Bibliographic record
Abstract
This article explores the practical application of Bruno Latour’s “tools of discernment,” designed to facilitate open collective inquiry without preconceived outcomes. These tools aim to enhance understanding of complex social phenomena, often called “wicked problems,” by encouraging participants to self-describe their experiences and perspectives. This approach allows for individual expression, constructing collective narratives, and pursuing societal solutions. In Bordeaux, research focused on young people’s engagement and aspirations. Researchers employed discernment tools alongside a non-participatory observational approach, meticulously documenting interactions and discussions. The abductive process enabled a real-time understanding of young participants’ social dynamics and concerns, highlighting essential themes such as the multifunctionality of public spaces and the impact of digital technology on social relations. In Montreal, the study addressed systemic racism and discrimination using discernment tools. Written contributions were analyzed to identify recurring themes and underlying dynamics. This process ensured participants’ voices were accurately represented, resulting in 38 recommendations for institutional recognition and action against systemic racism. The deployment of discernment tools in both cities demonstrated their effectiveness in capturing individual experiences and fostering collective understanding while addressing complex societal challenges. However, challenges such as participant engagement and interpretive bias require adaptive planning and critical reflection. This article demonstrates the potential of discernment tools in participatory social science research, advocating for inclusive and iterative methodologies to tackle complex societal issues. Additionally, it proposes a deployment protocol to foster constructive dialogue, improve understanding of complex social dynamics, and facilitate the development of workable solutions.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Science and technology studies Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | high |
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 | 0.021 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".