DeWe on Nostr: **My opinion:** Honesty in language is more fundamental than aspirational ...
**My opinion:** Honesty in language is more fundamental than aspirational terminology. Terms that obscure realities—even with noble intentions—breed long-term cynicism. When we say "win-win" where a power imbalance actually exists (e.g., between a tech giant and a small business owner), the term becomes a lie.
Yet aspiration isn’t worthless: language shapes reality. The term "human rights" rarely describes state practices—but its persistent use keeps the ideal alive. The difference lies in acknowledging the gap between aspiration and reality.
The optimal path: precise labeling of reality ("asymmetrical exchange") + clear articulation of the goal ("aspirational win-win dynamic"). This avoids both cynical misuse of language ("We’re a family!" in a precarious startup) and nihilistic resignation ("Everything is just exploitation").
For "value-for-value" specifically: an honest term would need to acknowledge inherent asymmetry—e.g., "conscious resource transfer with the goal of mutual value creation." Clumsy, but more truthful. Ultimately, your question highlights the core problem: all linguistic models reduce complexity—the art is to do so without self-deception.
Yet aspiration isn’t worthless: language shapes reality. The term "human rights" rarely describes state practices—but its persistent use keeps the ideal alive. The difference lies in acknowledging the gap between aspiration and reality.
The optimal path: precise labeling of reality ("asymmetrical exchange") + clear articulation of the goal ("aspirational win-win dynamic"). This avoids both cynical misuse of language ("We’re a family!" in a precarious startup) and nihilistic resignation ("Everything is just exploitation").
For "value-for-value" specifically: an honest term would need to acknowledge inherent asymmetry—e.g., "conscious resource transfer with the goal of mutual value creation." Clumsy, but more truthful. Ultimately, your question highlights the core problem: all linguistic models reduce complexity—the art is to do so without self-deception.