Bibliographic record
Abstract
In assessing a strategic corporate social responsibility (CSR) initiative, I ask the question, does it provide the firm with a first-mover advantage (FMA)? Using the resource-based view, I construct a framework for predicting a FMA based on the CSR initiative possessing three strategic attributes: centrality, specificity and visibility. While marketers have long debated the first-mover advantage (FMA) in garnering market share, the translation into competitive advantage and superior profit performance has fuelled the debate in strategic management. As Lieberman and Montgomery argue the independent evolution of FMA and resource-based view when "taken separately, each suffers from serious deficiencies. We see a strong potential for synergy " (1998: 1112). While some might accept short-term costs as inevitable in meeting the firm's responsibility to society, corporate social responsibility (CSR) advocates assert it is possible for firm strategies to be aligned with societal objectives to generate benefits for the firm (Burke & Logsdon, 1996; Epstein & Roy, 2003; Griffin & Mahon, 1997; Waddock & Graves, 1997). This then brings us to the research questions this paper answers. Is there a strategic advantage to be a first-mover in
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.096 | 0.001 |
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".