MétaCan
Menu
Back to cohort
Record W7064529093

Beading a Response to Mining Research

2022· article· en· W7064529093 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueScholarship@Western (Western University) · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicElectrical and Electromagnetic Research
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousWork (physics)SustainabilityOrder (exchange)Traditional knowledge
DOInot available

Abstract

fetched live from OpenAlex

The research project I took part in was Dr. Elizabeth Steyn’s UNEP project. This project is focused on responsible and sustainable mining, terms which are not easily defined. To briefly explain, mining itself cannot be sustainable because the resources involved are not renewable. To mine sustainably we need to invest back into the communities impacted by mines, providing skills and knowledge that can be utilized even after mines close. The industry is responsible if the environment and all stakeholders are considered. My role in this project was to look at ways in which Indigenous communities in Canada are impacted by mining projects. I provided insight to the effects mining has on Indigenous communities so that Dr. Steyn and her team can apply this information to their work on the UNEP project.\nIn addition to this my research output consisted of a beading project inspired by my research work and the origins of Ode'imin, known as the Strawberry teaching. The particular teaching I referenced comes from elder Lilian Pitwanakwat of Curve Lake First Nation. The heart berry helps us understand the connection between the mind, body, spirit, and emotions. We need our heart to guide us in order to maintain personal balance. The heart berry also reminds us of reconciliation and teaches us how to maintain heartfelt relationships in our families and communities. I was able to use this teaching to reflect and understand my thoughts and emotions towards the dark side of mining, but also recognize the parts that are positive.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.157
GPT teacher head0.387
Teacher spread0.230 · 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