From informal practices to formal conduct: Which ethical practices and issues for French lobbying consulting?
Bibliographic record
Abstract
In France, lobbying consulting is at the same time a recent and not well received activity, conversely to the United States. The influence of public decision making is certainly a particularly sensitive occupation, at both managerial and societal levels. This is why ethics as applied to business can play a central role in its establishment. This paper examines the practices and issues of ethics in lobbying consulting. The chosen field in this exploratory study is France. The case of a lobbying consultancy firm is more specifically developed. A three month participant observation research is complemented by secondary data on the profession in France and in the United States, as well as on French, European, American and Quebec institutions. The results of this research are developed along two lines: 1. The practice of lobbying ethics differs according to age and degree of institutionalization of the profession in the country. In France ethics is informal and based primarily on exemplary, with a particularly low regulatory potential. 2. The stakes of ethics are both internal to the lobbying consulting profession, in its structuring from an emerging to an established profession, as well as external in the clarifying of its relationship with its stakeholders including customers, government and the civil society.
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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 | 0.014 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.022 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".