The past is never dead: the role of imprints in shaping social and environmental reporting in a post-communist context
Bibliographic record
Abstract
Purpose Mobilizing a theoretical framework combining institutional logics and “imprinting” lenses, this paper provides an in-depth contextualized analysis of how historical imprints affect social and environmental reporting (SER) practices in Romania, a post-communist country in Eastern Europe. Design/methodology/approach The authors conduct a qualitative field study with a diverse dataset including regulations, publicly available reports and interviews with multiple actors involved in the SER field in Romania. The authors follow a reflexive approach in constructing the narratives by mobilizing their personal experience and understanding of the field to analyze the rich empirical material. Findings The authors identify a blend of logics that combine local and Western conceptualizations of business responsibilities and explain how the transition from a communist ideology to the free market economy affected SER practices in Romania. The authors also highlight four major imprints and document their longitudinal development, evidencing three main patterns: persistence, transformation and decay. The authors find that the deep connections that form between logics and imprints explain the cohabitation of logics rather than their straight replacement. Originality/value The paper contributes by evidencing the role of imprints' dynamics in the institutionalization of SER logics. The authors claim that the persistence (decay) of imprints from a former regime such as communism hinders (facilitates) the institutionalization of Western SER logics. Transformation instead has more uncertain effects. The pattern that an imprint takes hinges upon its usefulness for business interests.
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 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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.031 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 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".