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Record W111008390 · doi:10.22230/jem.2004v4n2a277

Identifying indicators of community sustainability in the Robson Valley, British Columbia

2004· article· en· W111008390 on OpenAlex
John R. Parkins, Jeji Varghese, Richard C. Stedman

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Ecosystems and Management · 2004
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsCanadian Forest Service
FundersCanadian Forest ServiceU.S. Forest Service
KeywordsSustainabilityGeographyEnvironmental resource managementEnvironmental planningEcologyEnvironmental science

Abstract

fetched live from OpenAlex

This paper outlines a method of developing indicators of well-being in small, forest-based communities. It also describes some specific measures of well-being in a particular forest-based community in the Robson Valley Forest District, British Columbia. In this project, we attempted to strike a balance between relying on locally obtained information—collected through workshops, interviews, and a mail survey—and information obtained from the social science literature. We took a broad-based approach toward indicator development by identifying goals and indicators pertaining to the entire region. Our paper explores this theoretical orientation in some detail and then provides an account of the dialogical methods used to identify community-based indicators. Of the six community goals we identified, we discuss “maintaining community capacity” at length by examining the empirical data from five indicators and then drawing some conclusions about the status of community capacity in the Robson Valley.

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.

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)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.258
Threshold uncertainty score0.920

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.045
GPT teacher head0.378
Teacher spread0.333 · 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