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Record W4224212749 · doi:10.3390/land11040534

Using Photovisualizations to Gain Perspectives on River Conservation over Time

2022· article· en· W4224212749 on OpenAlexaboutno aff
Meryl Braconnier, Cheryl Morse, Stephanie Hurley

Bibliographic record

VenueLand · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsnot available
Fundersnot available
KeywordsRecreationTributaryGeographyNatural (archaeology)Work (physics)Environmental planningEnvironmental resource managementSense of placeArchaeologyPolitical scienceCartographyEnvironmental scienceEngineering

Abstract

fetched live from OpenAlex

The Missisquoi River originates in a densely forested, hilly, and lightly populated region in northern Vermont, USA, flowing north until it crosses the Canadian border. The upper American stretches of the river are federally designated as “Wild and Scenic” in recognition of its outstanding natural, cultural, and recreational values. This paper reports on the place-based and river-focused perspectives of rural residents who live and work along the Missisquoi River and its tributaries and who are the recipients of Vermont’s shifting river management strategies. The mixed methods research drew on participant observation, interviews, and interpretations of photovisualizations (PVZs). The PVZ method identified the different geographical imaginaries held by residents and conservation professionals, demonstrating that PVZs can be used as a method to foster dialogue about sense of place and conservation initiatives. Visual aids can help unveil the complex, temporal relationships between landowners and the adjacent waterways, which in turn influence participation in river restoration efforts.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.049
GPT teacher head0.373
Teacher spread0.324 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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