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The Role of Spirituality in the Decision-Making Process Related to Native Plant Restoration in a Southern Ontarian Aboriginal Community

2018· article· en· W3010795545 on OpenAlexaffvenueabout
Verena Kulak

Bibliographic record

VenueRural Review Ontario Rural Planning Development and Policy · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland and Wildlife Management
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMandateSpiritualityParticipatory action researchProcess (computing)Citizen journalismEnvironmental planningEnvironmental resource managementSociologyPolitical scienceGeographyMedicineLawEnvironmental scienceComputer scienceAnthropology

Abstract

fetched live from OpenAlex

This is a participatory research project with an Aboriginal community in Southern Ontario. My goal is to identify which species-at-risk are relevant to a community and to develop a strategy to restore biodiversity in a selected location with importance to that community. This research collaboration also includes the Gosling Research Institute of Plant Preservation (GRIPP), which has a mandate to reintroduce plants via tissue culture techniques. This study can help identify the role that spiritual connection to plants can have in the decision-making process regarding restoration of plants. The role of spirituality in environmental management is an understudied theme and my findings can enlighten future initiatives. One of the questions at this early stage of my research, is to determine the perceptions that a community has about the use of plant technology in general and cloning in particular, as means to restore land and maintain the spiritual connection to medicinal plants.

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)0.003
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.394
Threshold uncertainty score0.792

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0090.006
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.317
Teacher spread0.303 · 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
Published2018
Admission routes3
Has abstractyes

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