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Record W2122217487

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

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

Bibliographic record

VenueoURspace (University of Regina) · 2012
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Economics and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsPerceptionGovernment (linguistics)GeographyCounty governmentForestryEnvironmental planningPolitical sciencePublic administrationPsychology
DOInot available

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.200

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0060.003
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.229
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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