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Theory of change for the mineral Exploration - INFACT project

2020· article· en· W3083242054 on OpenAlexaboutno aff
Cathryn MacCallum, Jon Russill, Moritz Kirsch, Leila Ajjabou, Insiya Salam, Louis Bennet

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityBusinessPolitical scienceEcologyBiology

Abstract

fetched live from OpenAlex

The INFACT project aims to reinvigorate mineral exploration in Europe by engaging society and using new technology and research to improve mineral exploration practice. The consortium is formed of geo- and social scientists working together to achieve a new vision of mineral exploration. As a key part of INFACT, expert stakeholders from across Europe and other jurisdictions such as Australia and Canada have been engaged in a series of online and face to face discussions to determine and address identified challenges to exploration and a way to overcome them. Five key environmental and social challenges and barriers to exploration in Europe have been determined by INFACT through a mix of qualitative and quantitative research. These were (i) existing land use, (ii) the cost of mineral exploration, (iii) public perceptions and negative attitudes toward the exploration and mining industry, (iv) sustainability and the environment, and (v) governance and regulatory structures and processes. Through a series of workshops and interviews, discussing ways to address these challenges and barriers, a vision for mineral exploration and mining in Europe was created: Mining in Europe should contribute to local and regional sustainable development, enabling a low carbon economy through environmentally and socially acceptable extraction of critical raw materials(CRM). This will involve: The European Commission developing and enforcing rigorous and binding legislation with respect to all mineral exploration activities; Increased investment contribution for exploration of CRM within Europe; Exploration companies being required to adopt environmental and socially acceptable good practice; Increased awareness of the importance of mining to support a low carbon economy and improved public trust in the process; Creation of socio-economic shared value through adoption of multi-stakeholder collaborative planning and visioning; and Exploration companies achieving and maintaining a Social Licence to Operate; The work presented will determine a way to ensure socio-environmentally sustainable supply of raw materials and the key steps required to achieve this vision.

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)0.015
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.020
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.003
Science and technology studies0.0050.021
Scholarly communication0.0100.011
Open science0.0030.009
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0250.002

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 head0.146
GPT teacher head0.257
Teacher spread0.111 · 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 designTheoretical or conceptual
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
Published2020
Admission routes1
Has abstractyes

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