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Enregistrement W2946814192 · doi:10.1108/ijem-02-2018-0066

Transparent resource management

2019· article· en· W2946814192 sur OpenAlex

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Notice bibliographique

RevueInternational Journal of Educational Management · 2019
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueSchool Choice and Performance
Établissements canadiensWestern University
Organismes subventionnairesnon disponible
Mots-clésPublic relationsContext (archaeology)Government (linguistics)RevenueCorporate governanceResource (disambiguation)Resource management (computing)BusinessEconomicsPublic administrationPolitical scienceAccountingFinance

Résumé

récupéré en direct d'OpenAlex

Purpose Public education is an important institution in any democracy, and the significant resources invested form a critical pillar in its provision. The evidence used to manage said resources is, therefore, an important issue for education leaders and a matter public interest. The purpose of this paper is to consider the role education finance leaders in Ontario, Canada, and what types of evidence they are using, how they are being employed and how much priority is given to each. Design/methodology/approach The paper employs a review of Ontario’s K-12 education funding policies/reports, and interviews with five K-12 funding model experts/leaders – four business superintendents from school boards of varying sizes (based on enrollment) and one system leader (to introduce perspective from the two levels of governance in resource management) to understand how these experts use evidence to inform resource decision making. This sampling strategy was also grounded in a key assumption: School boards with larger enrollment – and consequently larger budgets – will have greater capacity to use all forms of evidence when managing resources, as the majority of board revenue comes from grants that are mostly based on enrollment. Findings The findings bring important definition and prioritization of evidence that inform leaders’ resource decision making in education. The results point to two tacit, normative, unacknowledged and, yet, competing evidence frameworks driving resource management. The government is the most influential, prioritizing strategic policy, performance data, fiscal context and professional judgment; values embedded in policy and research were mentioned only in passing, while local anecdotal types of evidence were given less priority. Compounding this challenge is that all sides in debates on school resource needs face issues of access to, transparency in the use of and the prioritization given to various evidence types. Research limitations/implications Governments, with the assistance of academics, should formally articulate and make public the evidence framework they use to drive resource decision making. All sides of the resource management debate need to value a wider range of evidence, notably evidence that speak to local concerns, to reduce information gaps and, potentially, improve on the effective delivery of local educational programming. Education finance researchers could help to address access gaps by distilling research on the effective use of resources in a manner that is timely, tailored to the fiscal climate and to system- or district-level readiness for the implementation of a particular initiative. Practical implications Resource management driven solely by “facts” can support student achievement outcomes and effective system operation, but alone will not satisfy local-level aspirations for education or inspire public confidence; a key ingredient for the sustainability of this public institution. The results could be used to improve the balance of “decent information” used to inform resource deliberations and establish a shared understanding across stakeholder groups to facilitate compromise. The current state of affairs has all sides in advancing claims for resource needs based on what they understand to be evidence all while portraying competing claims as uninformed, undermining public confidence in education. Originality/value The paper draws from interviews with business superintendents and a system-level funding model expert, both lesser studied leaders on this topic in the Canadian context; offers a clear articulation of the evidence frameworks at play and the priority given to each type and how they are being used; presents definition and prioritization of evidence from the perspective of leaders in the Canadian context (most of literature is from the USA) – experts acknowledge that resource knowledge is contextually contingent and insight generated from other contexts will help to advance the field.

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,817
Score d'incertitude au seuil0,997

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0040,000

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.

Tête enseignante Opus0,024
Tête enseignante GPT0,355
Écart entre enseignants0,331 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle