Substantive and symbolic strategies sustaining the environmentally friendly ideology
Bibliographic record
Abstract
Purpose The purpose of this paper is to longitudinally explore the symbolic and substantive ideological strategies located in ENGIE’s environmental discourse while considering the specific negative media context surrounding the company’s environmental activities. Design/methodology/approach Thompson’s (2007) and Eagleton’s (2007) theorizations are used to build an extended ideological framework to analyze ENGIE’s environmental talk from 2001 to 2015. Findings ENGIE drew extensively on a combination of symbolic and substantive ideological strategies in its annual and sustainability reports while ignoring several major issues raised in the press. Its substantive ideological mode of operation included actions for the environment, innovation, partnerships and educating stakeholders/staff, while its symbolic ideological mode of operation used issue identification, legal compliance, rationalization, stakeholders’ responsibilization and unification. Both ideological modes of operation worked synergistically to cast a positive light on ENGIE’s environmental activities, sustaining the ideology of a company that reconciles the irreconcilable despite negative press coverage. Originality/value This paper develops the notion of environmentally friendly ideology to analyze the environmental discourse of a polluting company. It is the first to use both Thompson’s and Eagleton’s ideological frameworks to make sense of corporate environmental discourse. Linking corporate discourse with media coverage, it further contributes to the burgeoning literature that interpretively distinguishes between symbolic and substantive ideological strategies by highlighting the company’s progressive shift from symbolic to more substantive disclosure.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.006 | 0.026 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".