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Record W63660683

Participatory Photography as a Means to Explore Young People’s Experiences of Water Resource Change

2013· article· en· W63660683 on OpenAlexaff
Jennifer Fresque-Baxter

Bibliographic record

VenueIndigenous policy · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsFlexibility (engineering)Participatory action researchResource (disambiguation)Citizen journalismContext (archaeology)SociologyCurriculumSuitePublic relationsPedagogyEnvironmental resource managementEnvironmental planningPolitical scienceGeographyComputer scienceManagement
DOInot available

Abstract

fetched live from OpenAlex

This paper highlights experiences from a participatory photography project undertaken with high school students in Fort Resolution, Northwest Territories. Working with local teachers, the project linked environmental change research with classroom-based curriculum objectives. The project explored the relationships young people have with their lands and waters, and documented their experiences of water resource change. Incorporating young people’s perspectives is a critical avenue for research because they have important observations in the here and now, and are future scientists and community leaders. As such, young people can play a key role in water decision-making in the territory. Engaging young people as active co-producers of environmental change knowledge in a research context requires unique and creative approaches. Participatory photography offers a means for expanding the current suite of tools to explore the relationships that young people have with water and place. Findings show that young people are keenly aware of how their waters are changing, and that they are concerned about the effects of these changes on engagement in land- and water-based activities. Outcomes and lessons, including the importance of student voice, flexibility and adaptability, and establishment of school-researcher relationships, are highlighted. The goal of this paper is to encourage researchers and policy-makers to expand their suite of tools for exploring person-place connections and to consider the important observations and experiences of young people in development of policies for use and protection of water.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.153
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.523
GPT teacher head0.568
Teacher spread0.045 · 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 teacher head, not a consensus.

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

Citations8
Published2013
Admission routes1
Has abstractyes

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