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Enregistrement W2122217487

Farmers' Perceptions of the Effectiveness of Government Programming at the Ground Level: A Manitoba-Saskatchewan Case Study Comparison

2012· dissertation· en· W2122217487 sur OpenAlexaboutno aff
Christina Marie Canart

Notice bibliographique

RevueoURspace (University of Regina) · 2012
Typedissertation
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueAgricultural Economics and Policy
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPerceptionGovernment (linguistics)GeographyCounty governmentForestryEnvironmental planningPolitical sciencePublic administrationPsychology
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

This thesis examines the perceived impact of agriculture programming at the ground level in the Rural Municipality of Albert in Manitoba, and the Rural Municipality of Storthoaks in Saskatchewan. It provides a description of agriculture as it was practiced in these communities in 2008, as well as an analysis of how producers perceived the outcome of three specific programs: the Canadian Agricultural Income Stabilization (CAIS) account, Production Insurance (PI) and the Environmental Farm Planning (EFP) program. The Agricultural Policy Framework, implemented in 2003, was the structure upon which these programs originated from. The research measures the effectiveness of the programs as perceived by producers and as compared to national program objectives. The thesis examines how programs occur at the ground level in two rural municipalities and explores whether or not the perceptions of agricultural programming differs between the communities. Program differences on the ground level can result from a number of factors. First, the negotiation process preceding the signing of agreements between the federal and provincial governments can create regional differences in the allocation of funding and program objectives as government priorities and needs are merged. In addition, the agency selected for program administration (e.g., federal government, provincial government or a third-party agency) can impact the level of uniformity in program outcome due to differences during program development. Furthermore, the manner by which the program is delivered and the challenges that accompany the implementation process can result in program variations. In the end, the same national program can have varied results. Specifically, differences were expected between the RMs in two of the three programs analyzed. The Canadian Agricultural Income Stabilization account was expected to have similar results due to Manitoba and Saskatchewan‟s reliance on the federal government for program administration. In comparison, Production Insurance and the Environmental Farm Planning program were administered by different agencies as a result of the federal-provincial agreements. It was in these circumstances that differences in program outcomes were expected. Case study communities were selected based on their similarities in order to allow for program differences between the RMs to become evident. A questionnaire survey was conducted in 2008 to solicit information from producers, with additional data obtained from Statistics Canada and government documents. The perceived effectiveness of government programming in meeting program objectives varied. The Agricultural Policy Framework outlined a total of 22 objectives for the three programs under investigation. The Canadian Agricultural Income Stabilization account was identified as „ineffective‟ in meeting all of its objectives. Respondents perceived Production Insurance and the Environmental Farm Planning program as being „somewhat effective‟ in meeting program objectives at the ground level. Results indicated similar outcomes between the RMs in 20 of the 22 objectives. This research showed that provincial location played a minimal role in the outcomes of programs as they differed between RMs. In fact, program outcomes were found to be similar in most circumstances. For those objectives that were deemed as „ineffective‟, the research offers producer feedback in an effort to explain the occurrences.

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)0,002
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,067
Score d'incertitude au seuil0,200

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,004
Études des sciences et des technologies0,0060,003
Communication savante0,0030,001
Science ouverte0,0010,002
Intégrité de la recherche0,0010,001
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 Opus0,022
Tête enseignante GPT0,229
Écart entre enseignants0,207 · 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'étudeQualitatif
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
Publié2012
Routes d'admission1
Résumé présentoui

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