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Record W6903209266 · doi:10.7939/r3n01010k

A Public Policy Advocacy Project to Promote Food Security: Exploring Stakeholders’ Experiences

2014· dissertation· en· W6903209266 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2014
Typedissertation
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsnot available
Fundersnot available
KeywordsParticipatory action researchFood securityPolicy advocacyThematic analysisCitizen journalismPublic policyAction planParticipatory evaluationIdentification (biology)Qualitative property

Abstract

fetched live from OpenAlex

Food security is said to exist “when all people, at all times, have physical and economic access to sufficient, safe, and nutritious food that meets their dietary needs and food preferences for an active and healthy life” (Food and Agricultural Organization, 2008, p. 1). In the last several decades, challenges related to the achievement of food security in Canada have had a significant impact on public health. To address such challenges, comprehensive approaches are required, which include action at the public policy level. In this study, I worked with stakeholders from Growing Food Security in Alberta’s policy working group to develop a public policy advocacy project to promote food security in Alberta. I also explored the experience of this group as it engaged in this process. This study was informed by principles of community-based participatory research (CBPR) and a focused ethnographic approach. In total, 14 stakeholders from across Alberta participated in the study. Data generation included semi-structured interviews, participant observation, and document review. Data analysis took two forms. First, I arranged data chronologically to document and describe the advocacy project. Second, I conducted a thematic analysis to explore stakeholders’ engagement experiences. Development of the advocacy project involved three phases carried out between November 2012 and July 2013: (a) an initial workshop to begin the identification of our advocacy focus; (b) monthly meetings to develop the advocacy project, and; (c) a final workshop to summarize outcomes and develop a plan for project sustainability. During this process, the group engaged in advocacy steps informed by CBPR approaches to policy advocacy, including issue identification, determining our advocacy focus, research and information gathering, developing our position, strategic analysis, and organizing for action (Themba-Nixon, 2010). The result of the advocacy project was the beginning of a campaign calling on the Alberta government to develop a Universal School Food Strategy. Through the exploration of stakeholders’ experiences, I identified four main themes. The first theme explores the research project as a positive and open space to contribute, the second theme focuses on diversity and achieving common ground, the third theme describes the group’s sense of confidence and capacity throughout the project and, finally, the fourth theme highlights the group’s experience of uncertainty. Contextual factors identified include the meeting mode, time, and meeting organization. I end the study with a critical reflection on our advocacy focus, as well as highlights and lessons learnt from the advocacy project. I also situate the exploration of stakeholders’ experiences in relation to the literature. Last, I provide recommendations for future research and action. Taken together, findings and recommendations from this study may help to inform advocacy work to promote food security in other Canadian jurisdictions.

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)0.017
metaresearch head score (Gemma)0.012
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.760
Threshold uncertainty score0.478

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0390.019
Scholarly communication0.0090.006
Open science0.0030.013
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0030.000

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 head0.268
GPT teacher head0.368
Teacher spread0.100 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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