Editorial: Networks and knowledge brokering: advancing foundations, inviting complexity
Notice bibliographique
Résumé
Across this special issue, the contributing articles illuminate how knowledge brokerage and relational networks can be harnessed-and sometimes challenged-to strengthen evidenceinformed policy and practice in education. Their findings offer new insights into the interplay of theoretical concepts, methodological approaches, and ethical imperatives that shape this complex terrain. Several contributions highlight the distinctive roles and practices of knowledge brokers. For instance, Malin and Shewchuk (2024) emphasize that knowledge brokers are not merely neutral intermediaries; rather, they are "actors whose activities and decisions must be understood contextually-e.g., in relation to the communities that are being connected and to brokers' placement within systems" (p. 3). Similarly, Caduff et al. (2024) explore how brokers' relational ecosystems both broaden and constrain their ability to mobilize resources and facilitate innovation through the strong and weak social ties they cultivate.In pushing beyond conventional frameworks, some articles spotlight relational networks as sites of strategic innovation. Bohannon et al. (2024) demonstrate how boundary infrastructures, such as co-designed professional learning opportunities and flexible organizational routines, help rural districts adapt and learn in dynamic contexts. Turner et al. (2024) extend this line of thought by mapping social networks related to mental health supports in schools. Their analysis reveals how patterns of interaction and trust-building open or close pathways for critical knowledge flows.Equity and ethics also figure prominently. Malin and Shewchuk (2024) advocate for an equity-centered lens, urging brokers to foreground issues of representation, power, and justice in their work. This stance resonates with Friesen and Brown's (2024) exploration of teacherleaders' professional learning, where the growth of confidence and capabilities is tied closely to the careful, context-sensitive design of relational activities that honour diverse perspectives.Methodologically, these studies introduce varied research designs-ranging from social network analysis to in-depth qualitative case studies-that yield a rich understanding of how knowledge moves through and transforms educational ecosystems. Collectively, the articles underscore a need for more approaches that capture complexity rather than oversimplify.In terms of implications, the authors suggest that policymakers, leaders, and practitioners who aim to strengthen ties between research, policy, and practice must attend to the subtleties of relationships, resources, and values. Rather than a technical fix, advancing equitable and impactful knowledge brokerage requires sustained reflection, dialogue, and openness to contextspecific adaptations.In recent years, scholars and practitioners have recognized that addressing complex issues-ranging from mental health supports in schools to rural capacity-building-cannot be achieved by simplistic, top-down evidence dissemination alone. There is a renewed emphasis on building relational infrastructures that acknowledge the multi-level interplay of policies, practices, and diverse forms of expertise (MacKillop et al., 2020). The articles presented in this research topic both reinforce and deepen this perspective. By examining relational ecosystems, boundary infrastructures, and equity-centered approaches, they suggest that knowledge brokerage and relational networks are integral elements of educational change, not just beneficial add-ons. Their collective insights resonate with an emerging scholarship that views relational networks as essential to leveraging complexity and mobilizing knowledge in service of local and global educational aims (Penuel et al., 2020;Rodway et al., 2021).For policymakers and practitioners, these findings imply that designing more flexible, equity-aware systems is crucial. Rather than imposing standardized reforms, leaders might consider strategies such as co-designing professional learning that respects multiple knowledge systems and power differentials. Such approaches can help ensure that local expertise is not overshadowed by distant authorities-a point highlighted when Bohannon et al. (2024) found that "even the best-intentioned external partners must negotiate shared ownership with rural educators" (p. XX).For researchers, there is a fertile landscape for future inquiries. Comparative, crossdisciplinary work could elucidate how relational networks evolve in varying socio-political contexts. Longitudinal research might track the lasting impacts of network-based interventions, while other methods-such as critical ethnographies or participatory action research-could surface subtle power imbalances that shape learning processes over time. These studies prompt a renewed attentiveness to the human, relational dimension of educational change. The educational challenges faced worldwide call for approaches to change that value complexity and contextual nuance. By continuing to explore this terrain and by refining methodologies to capture the contours and dimensions of knowledge brokerage in relational networks, educational communities can move closer to realizing meaningful, sustained improvements that are both evidence-informed and locally resonant.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,024 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».