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Record W4390395844 · doi:10.21203/rs.3.rs-3817875/v1

Exploring Economic Adaptations: Qualitative Insights into the Metal Industry Amidst Shifting Towards Renewable Energy

2023· preprint· en· W4390395844 on OpenAlex
Samantha Reynolds, Lily Anderson

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.

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsBusinessSupply chainIndustrial organizationDiversification (marketing strategy)Thematic analysisSustainabilityRenewable energyTransformative learningQualitative researchMarketingEngineeringSociology

Abstract

fetched live from OpenAlex

Abstract This qualitative study delves into economic adaptations observed within the metal industry in response to the transition towards renewable energy sources. Through semi-structured interviews with key industry stakeholders, the research aimed to uncover strategic shifts, challenges, and opportunities encountered by metal companies amid this transformative phase. The methodology involved in-depth semi-structured interviews, allowing for comprehensive exploration of experiences, perspectives, and strategic maneuvers within the metal industry. Thematic analysis of these interviews offered insights into how companies are adapting their practices to align with the demands of renewable energy technologies. Findings from the study revealed a deliberate shift in the industry's focus towards critical metals essential for renewable energy applications, such as lithium and rare earth elements. This adaptation involves significant investments in retooling production lines and exploring novel extraction methods to meet the burgeoning demand. Challenges related to ensuring a resilient supply chain emerged prominently. The industry faces risks associated with geopolitical tensions and market fluctuations, prompting the exploration of diversified sourcing strategies and alternative reserves to fortify the supply chain against disruptions. The study's limitations lie in its qualitative nature, limiting broader quantitative assessments, and the snapshot nature of the research, capturing dynamics at a specific time frame. Practically, the research offers valuable insights for industry stakeholders, guiding strategic decision-making, supply chain fortification, and market diversification efforts. Socially, the alignment of the industry with renewable energy transitions holds promise for enhanced sustainability and reduced environmental impacts. This study contributes original insights into economic adaptations within the metal industry amidst the shift towards renewable energy sources, offering a nuanced understanding of industry responses and their implications. However, the qualitative approach may limit generalizability, and continuous monitoring is necessary to track long-term industry trends.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.624
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.376
GPT teacher head0.442
Teacher spread0.065 · 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