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Record W7001268223

From Innovation to Codification: Conversations with Iskatewizaagegan Elders Regarding Creativity, Memory and Plants in Anishinaabe Society

2009· article· en· W7001268223 on OpenAlexaffabout

Bibliographic record

VenueDigital Library Of The Commons Repository (Indiana University) · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicIndigenous Knowledge Systems and Agriculture
Canadian institutionsUniversity of ManitobaAssembly of First Nations
Fundersnot available
KeywordsIndigenousTraditional knowledgeTerminologyProcess (computing)Psychological resilienceResource (disambiguation)Task (project management)DocumentationConceptual frameworkModernization theory
DOInot available

Abstract

fetched live from OpenAlex

"Ethnoecologists have provided extensive documentation of the knowledge held by many indigenous communities regarding places and the relationships among the beings of a place. Ethnobotanists have undertaken a similar task in locating plants within social, cultural and ecological systems. However, this work has often characterized indigenous people as holders of knowledge sets in imminent danger of being eroded through the forces of modernization and globalization. Theoretical models, rooted in complexity theory, have begun to influence ethnoecological and ethnobotanical understandings of the dynamics of knowledge systems. These models are exploring the institutions and processes of socialecological networks that allow for innovation while conserving the linkages between the past and the future. \n \n "This paper is based upon ethnobotanical and ethnoecological research undertaken with Anishinaabe people of Iskatewizaagegan No. 39 Independent First Nation located in northwestern Ontario, Canada. The purpose of this paper is to develop some working terminology and a conceptual model to explore the dynamics and resilience of social-ecological systems. One of the missing pieces in the resilience literature is the inclusion of individuals into the process of adaptive learning. The adaptive learning model proposed in this paper links the individual process of creativity to the social processes by which new information can become encoded within the institutions and collective information of a knowledge system. My goal for this conceptual model is to provide a way to think about the dynamics of contemporary indigenous systems of resource management in a manner that allows for innovation and self- determination. This is necessary to free our minds from the shackles of the conservative models proposed by many conservation groups which attempt to freeze indigenous people and lands in an idealized form. The model explored in this paper is intended to allow for the individual creativity to from the basis of adaptive learning while respecting the memories of a society."

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)0.004
metaresearch head score (Gemma)0.004
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 score0.875
Threshold uncertainty score0.249

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0220.017
Scholarly communication0.0050.005
Open science0.0010.007
Research integrity0.0030.004
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 head0.008
GPT teacher head0.154
Teacher spread0.147 · 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
Published2009
Admission routes2
Has abstractyes

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