Using a Community of Practice Approach to Respond to Food Insecurity During the COVID-19 Pandemic in Edmonton, Alberta
Notice bibliographique
Résumé
Hunger and food insecurity have a long history and prevalence, with the oldest food bank in Canada and hundreds of community agencies responding to food insecurity. This research began in partnership with the Community University Partnership (CUP) at The University of Alberta to support network building in this sector. As the COVID-19 pandemic emerged, food insecurity increased and all levels of government responded with increased availability of funding for responding to food insecurity. This funding also allowed for new organizations to enter the food insecurity response sector in Edmonton. The City of Edmonton then responded to this change in the sector by hosting a table on the collaboration and coordination of food insecurity responses, involving several community agencies. The focus of this research shifted in partnership with what this research calls “The City Table” to support their network and community building process. This research asks: how can the experiences of community agencies, donors and funders inform the building of a collaborative response to food insecurity during crises? Qualitative interviews were used to gain a depth of understanding in this sector, which was then supplemented by the insights gained through participation at The City Table to create an iterative community based research process. Elven interviews were conducted with professionals representing community agencies, donors of food and funders, and were selected based on the depth and richness of their anticipated insights, as informed by the research’s active involvement with this sector in a “snowball” approach. Drawing from the literature on the formation of communities of practice, the themes of engagement, imagination and alignment were used to guide the analysis of the data collected. The research found that this sector has the beginnings of forming a community of practice as a learning community that may support collaboration on responses to food insecurity. However, competition between agencies for funding and donations, as well as unstandardized data collection in the sector were identified as obstacles to the community of practice process. Further research is recommended in bridging the learnings generated by other poverty response sectors in Edmonton, particularly the housing insecurity sector, to gain insights into supporting the community of practice process.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,027 | 0,022 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,030 | 0,014 |
| Communication savante | 0,011 | 0,004 |
| Science ouverte | 0,007 | 0,016 |
| Intégrité de la recherche | 0,004 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 source (Gemma direct ou Codex distillé), 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 ».