Representation in Systems Development and Implementation: A Healthcare Enterprise System Implementation
Notice bibliographique
Résumé
Today’s information systems are often large and complex, affecting many people within and beyond the organization. Participation in this context is increasingly challenging because of the complexity of involving all who might be affected by a new information system. As a result, systems of representation, in which individuals are chosen to represent others, are often put in place to manage the participation process. Research has considered particular challenges of “representative participation” (Mumford, 1983); however, there is little empirical research comprehensively examining these systems of representation. Who participates in these systems, how are they structured and how is this representative work undertaken? Most importantly, what are the impacts of these decisions on the representation systems that are built and on the participation that flows from them? The purpose of our research is to explore the structuring of systems of representation in IS development and implementation. Building on the work of Land and Hirschheim (1983) and Mumford (1983), and drawing on Habermas’ deliberative democracy (1998), this research explores the system of representation employed in a large Electronic Health Record implementation as empirical evidence. Healthcare is a critical context for studying information systems implementation because of its uniqueness and complexity (Chiasson and Davidson, 2004; LeRouge et al., 2007), and therefore serves as an important environment for this research. Our contributions, drawn from this Electronic Health Record project, include an understanding of three fundamental tasks for developing systems of representation: defining the constituency, selecting representatives, and determining how the representation relationship will be carried out. We demonstrate that systems of representation can be classified by different meanings of “represent.” These types – “represent as spokesperson,” “represent as example” and “represent as symbol” – differ in the purpose of representation, in who is involved and in how representation is undertaken. Most importantly, these types of systems differ in their participatory potential. The findings highlight the opportunities and challenges inherent in the construction and implementation of systems of representation. The paper concludes by exploring the implications of these findings for practitioners and researchers, suggesting that representation should be more than simply appointing representatives, and offering mechanisms for participation and influence. We call on researchers to view these systems of representation in more fine-grained ways to better understand what their complexities mean for contemporary system development and implementation.
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 | 0,061 | 0,036 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,010 | 0,030 |
| Communication savante | 0,017 | 0,019 |
| Science ouverte | 0,003 | 0,017 |
| Intégrité de la recherche | 0,007 | 0,008 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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 ».