Businesses for Middle East peace‐building: a framework for engagement
Bibliographic record
Abstract
Purpose This paper outlines a framework for engaging international business in the Palestinian‐Israeli peace process, based not on traditional profit models but on corporate social responsibility (CSR). Design/methodology/approach A crucial ingredient to Middle East peace is an economic development process providing jobs, stability, and growth in the West Bank and Gaza. This paper reports on a 26 member consultation at Windsor Castle, England, convened by the Institute for Global Ethics (IGE) in September 2002 to bring together Palestinians and Israelis from the region with business leaders and professionals from Europe, the US, and Canada. The consultation was preceded by an IGE research paper and followed by a published report. Findings A discussion of the arguments for CSR engagement in the Middle East, along with two key documents agreed by the participants, are reported here. A “statement of principles” identifies six traits of successful CSR activities in the region. The second, listing 21 “practical steps for promoting economic development,” identifies potential business interventions listed in descending order of risk, complexity, cost, and long‐term commitment, including such items as “create micro‐enterprise opportunities for local entrepreneurs, and commit to purchasing their outputs,” and “help create management and/or skills training programs within the region.” The participants strongly agreed that the global business community, acting within a CSR framework, could significantly advance the prospects for Middle East peace. Originality/value This paper will interest business executives, CSR proponents, diplomats and economists, and leaders within the region seeking ways to jump‐start the currently stalled peace process.
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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 | 0.047 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.024 | 0.075 |
| Scholarly communication | 0.030 | 0.027 |
| Open science | 0.004 | 0.030 |
| Research integrity | 0.015 | 0.014 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".