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Enregistrement W6912846365 · doi:10.5281/zenodo.820609

Evaluation Framework For Cic'S Settlement Programs

2004· article· en· W6912846365 sur OpenAlexaboutno aff

Notice bibliographique

RevueZenodo (CERN European Organization for Nuclear Research) · 2004
Typearticle
Langueen
DomaineDecision Sciences
ThématiqueEvaluation and Performance Assessment
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésSettlement (finance)Service providerLogic modelService (business)Process (computing)StakeholderNegotiationService delivery framework

Résumé

récupéré en direct d'OpenAlex

[In 2004] Citizenship and Immigration Canada (CIC) is in the process of evaluating all of its national settlement programs. This report lays out an evaluation framework and logic models for CIC’s programs, and defines some key questions that will guide the program evaluations. The framework aims to clarify the desired results of CIC’s settlement programs for their many stakeholders – CIC staff, Service Provider Organizations (service providers), evaluators, and senior members of the federal government. Like all frameworks, it should be revised and updated as new research expands current knowledge of what interventions lead to successful settlement and integration. Stakeholder groups will use this framework in different ways: CIC staff at National Headquarters will use the framework to define the requirements for evaluations for the settlement programs in 2004. In addition, the output variables and activities contained in the framework may lead to revisions of some iCAMS variables to reflect changes in activities and recommended outputs. CIC staff in the Regions can use the framework to guide contribution negotiations with service providers. For example, service providers who can demonstrate success in key immediate outcomes may be able to make a case for increased funding by meeting CIC objectives for greater service effectiveness. Service Providers can use the framework to help them develop data collection processes that will allow them to demonstrate success in meeting program outcomes. Service providers can also use the program logic models to review their service delivery models so that their activities lead logically to desired immediate outcomes. The first draft of the evaluation framework for CIC’s settlement programs was written in 1999/2000. Since then the framework has been significantly revised, based on dozens of meetings, workshops and conversations with service providers and CIC staff. Interviews with key informants and a review of the literature on settlement and labour market integration also contributed to the revisions. The evaluation framework for LINC was discussed in workshops with service providers in the fall of 2003, and a similar exercise (involving 14 workshops across the country) was carried out for the ISAP and Host programs in February and March 2004. The program logic models in Section 5 distill hundreds of comments and suggestions into four highly simplified diagrams. Following are some key issues that should be kept in mind while reviewing this document. · It is long past time for the social services to evaluate themselves critically, and the settlement sector is no exception. The transition towards accountability and results-based management, while challenging, is essential for the achievement of Canadian policy objectives as well as the individual goals of newcomers themselves. Service providers across the country acknowledge the importance of this process, and generally welcome the opportunity to demonstrate and improve their effectiveness. · On the other hand, data collection is time-consuming for service providers, and should be minimized as much as possible while meeting accountability requirements and evaluation objectives. A common mistake for both funders and service providers is to gather data elements that don’t lead directly to better services or improved impact, but instead reduce efficiency by taking up scarce time. This evaluation framework attempts to minimize data collection to measures that will have a real benefit on improving services to clients and enabling CIC to manage agency performance. · In particular, indicators of intermediate and long term outcomes are expensive to collect and difficult to validate. Over the next few years, starting with the upcoming evaluations, both CIC and service providers should develop and begin collecting meaningful and valid indicators to create a baseline for evaluating settlement programs in the future. CIC should identify service providers and researchers that have demonstrated leadership in this area, and work with them to enhance the capacity of the settlement sector to evaluate itself. Section 5 of this paper – Settlement Program Logic Models – is intended to be used as a stand-alone summary of the evaluation framework. It contains the logic models for all three programs, the logic model for CIC’s settlement programs as a whole, and a few notes on 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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,148
score de la tête « metaresearch » (Gemma)0,078
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
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 enseignants0,148
Score d'incertitude au seuil0,784

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,1480,078
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0020,004
Bibliométrie0,0100,007
Études des sciences et des technologies0,0060,007
Communication savante0,0180,008
Science ouverte0,0060,004
Intégrité de la recherche0,0060,006
Charge utile insuffisante (le modèle a refusé de juger)0,0090,002

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 Opus0,290
Tête enseignante GPT0,459
Écart entre enseignants0,169 · 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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2004
Routes d'admission1
Résumé présentoui

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