Corporate Reporting of Cross-Sector Alliances: The Portfolio of NGO Partners Communicated on Corporate Websites
Bibliographic record
Abstract
Abstract Nongovernmental organization (NGO)–corporate alliances are a strategic type of institutional positioning communication. From a sample of 155 US Fortune 500 corporations and 695 NGOs drawn from corporations' websites, this research examines: (a) the number of NGOs with which corporations communicate alliances; (b) the patterns of communicated alliances that exist between corporations in economic industries and NGOs in social issue industries; and (c) the relationship between corporate stakeholders and the communication of alliances with NGOs in particular social issues. This research tests the propositions of Symbiotic Sustainability Model concerning the number and type of NGO alliances likely to be communicated by corporations. In particular, this research demonstrates that most corporations only communicate alliances with a few NGOs and with one NGO in an issue industry. In addition, the results suggest that corporations in the same economic industry are likely to communicate alliances with different NGOs in the same issue industries. In combination, these findings imply that a small set of social issues are likely to be included in NGO–corporate communication. Exploring this implication, this research reports preliminary findings about communicated alliances between corporations in 11 economic industries and NGOs in 59 social issue industries. Keywords: Symbiotic Sustainability ModelInterorganizational NetworksCorporate Social ResponsibilityNGO Acknowledgements The authors would like to thank Cynthia Stohl and M. Scott Poole for their helpful feedback on an earlier version of this manuscript. The authors would like to also extend thanks to the anonymous reviewers that offered many helpful suggestions to improve this manuscript. In addition, the authors would like to thank Mark Meister for serving a third independent coder and Jon Pike, Justin Lipp, Amy Dobler, and Charles Matson for their help in printing the websites. A version of this paper was presented at the 2008 International Communication Association Conference in Montreal. Notes 1. http://cms.komen.org/komen/Partners/BecomeaPartnerorSponsor/index.htm 2. http://cms.komen.org/komen/Partners/index.htm 3. http://www.aa.com 4. http://www.yoplait.com 5. An inverted-J describes a distribution in which most corporations have a very small out-degree and only a few organizations have a large out-degree. It is similar to a power-law distribution but is less restrictive (see Simon, Citation1955). 6. Media impressions are "the sum of the exposures to the entire media plan" (O'Guinn, Allen, & Semenik, Citation2006, p. 497). Additional informationNotes on contributorsMichelle Shumate Michelle Shumate, University of Illinois, Urbana-Champaign, USA Amy O'Connor Amy O'Connor, North Dakota State University, USA
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".