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Record W7015350635

Stakeholder Engagement in the Steel Industry: The key to unlocking the resources and markets of tomorrow, today

2008· other· en· W7015350635 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

VenueNottingham ePrints (University of Nottingham) · 2008
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsStakeholderStakeholder engagementVisionKey (lock)Stakeholder analysisConsumption (sociology)Revenue
DOInot available

Abstract

fetched live from OpenAlex

The emergence of developing countries, specifically Brazil, Russia, China and India, is pushing the demand for steel to new heights. This comes at the same time as steel consumption is decreasing in developed markets such as the USA and Canada, emphasizing the importance these new markets are having on the growth of the steel industry. As leaders in the steel industry, both in terms of revenue and output, this is especially important for ArcelorMittal. With a growth strategy that relies heavily on vertical integration, entry into new markets and accessing the resources they contain is essential to the future success of the company. However, these markets and the resources within them are controlled by various stakeholder groups, whose expectations and visions are often conflicting but who can collectively determine whether or not ArcelorMittal's plans go forward. Thus it is imperative that ArcelorMittal proactively engages with these stakeholders and involve them in its decision making processes as this will increase the likelihood of it gaining access to resources and entry to new markets and possibly result in a sustained competitive advantage. Currently, there appears to be a gap in how effective ArcelorMittal's current stakeholder engagement strategies are perceived to be by some stakeholder groups, a perception that whether or not is justified, could jeopardise ArcelorMittal's 'social licence' to operate. After building a business case for stakeholder engagement and then analyzing and discussing this perceived gap and its implications for the company, this study puts forward recommendations that will help ArcelorMittal identify relevant stakeholder issues and then effectively engage on them, recommendations that include: \n-\tDeveloping a system for indentifying internal and external stakeholders, both at a global level and at a local level, and then classify them based on their importance to the company's business strategy\n-\tDevelop global and local stakeholder engagement strategies that emphasize proactive, two-way communication\n-\tEnter into more partnerships with NGOs and Industrial Bodies in an effort to gain insight into current best practices for stakeholder engagement, especially in the mining sector\n-\tUtilise the internet and intranet to develop interactive engagement tools that can also provide customised information for specific stakeholder groups\n-\tDevelop an online resource centre for ArcelorMittal's Corporate Responsibility practitioners that provides relevant materials and tools needed in order to create and implement local stakeholder engagement plans

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.188
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0030.002
Research integrity0.0010.003
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 head0.056
GPT teacher head0.237
Teacher spread0.181 · 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