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Understanding the Importance of Place in Wrongdoing: Examining Banro’s Activities in South Kivu

2025· article· en· W4416006471 on OpenAlexaboutno aff
Shawn L. Berman, Michael E. Johnson‐Cramer, François Lenfant, Manuel R. Montoya, Michelle Westermann‐Behaylo

Bibliographic record

VenueAcademy of Management Proceedings · 2025
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousContext (archaeology)HarmAction (physics)Work (physics)DemocracyIdentity (music)Field research

Abstract

fetched live from OpenAlex

This paper explores cultural context as a mediating mechanism between macro-level efforts to govern corporate responsibility and micro-level organizational actions. Building on previous work seeing organizational wrongdoing as a socially constructed process, we argue that a disconnect often arises between Western legalistic frameworks and the cultural contexts of indigenous communities. This disconnect creates a jurisdictional void that fosters organizational wrongdoing. Theoretically, we emphasize the importance of understanding the “identity of place” as a key factor in addressing this issue, offering a corrective to placeless organizational practices. Using field research on the resettlement efforts of the Canadian mining company Banro in the Democratic Republic of Congo, we examine how the company’s disregard for local cultural identity led to significant harm in the community and fueled further irresponsible behaviors. We conclude with scholarly and practical implications for preventing conflict and wrongdoing, particularly as Western institutions promote transnational frameworks addressing societal grand challenges.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.417
Threshold uncertainty score0.621

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.046
GPT teacher head0.244
Teacher spread0.197 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2025
Admission routes1
Has abstractyes

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