Creolization as resistance to PCSR: The contested field of the past at the Guiana Space Center
Bibliographic record
Abstract
Various types of organizations are confronted to the challenge of engaging in CSR with stakeholders who hold the memory of their past irresponsible actions and consequently remain hermetic to any attempt to improve relations. This paper sheds light on how a negative shared past continues to shape the present and future relations of an organization in the European space industry and the local community in which it is embedded. Longitudinal data covering a 50–year period show how the past is a contested field–i.e. what should be remembered or forgotten–which is continually revived and hinders the improvement of relations despite increasing engagement in CSR from the organization. While no overt confrontation can be observed between the organization and the local community, the latter maintains a collective memory of the past through a process of Creolization–i.e. the capacity of an extremely diverse set of people to invent a new and unique culture through the daily practice of togetherness. As a process of invisible resistance, Creolization brings new insights on how uncoordinated stakeholders can undermine any effort to implement CSR. This paper contributes to the political CSR (PCSR) literature which focuses on the contribution of business organizations to the provision of public goods through their CSR initiatives. More specifically, the paper uncovers the non-visible yet undermining role of stakeholders who resist their inclusion in the governance of CSR, and proposes a creolized conception of PCSR that unveils the agency of marginalized stakeholders.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.016 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".