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Record W7092625880 · doi:10.5281/zenodo.17391232

爱的证明:治理 AI 和人类文明的共识机制

2025· report· cmn· W7092625880 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typereport
Languagecmn
FieldSocial Sciences
TopicInnovation, Sustainability, Human-Machine Systems
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsMeaning (existential)Foundation (evidence)Corporate governanceValue (mathematics)Work (physics)Civilization

Abstract

fetched live from OpenAlex

本文提出了面向 AI 与 Web3 时代的全新治理共识——“爱的证明(Proof of Love, PoL)”。作者认为,爱——作为共情、互惠与创造性合作的伦理力量——是当代技术文明所缺失的核心原则。论文融合区块链治理、去中心化激励机制与伦理哲学,探讨如何以“爱”作为文明共治的新基石,让人类与 AI 在共享价值创造中实现共生。该研究跨越哲学、经济学与系统设计,旨在重新定义智能、治理与文明的意义。 This paper proposes Proof of Love (PoL) as a new ethical and governance consensus for the age of AI and Web3. It argues that love—understood as empathy, reciprocity, and creative cooperation—is the missing principle in current technological civilization. By integrating blockchain governance, decentralized incentives, and ethical philosophy, the study outlines how PoL can serve as a foundation for a new “Love-based Civilization,” where human and AI co-govern through shared value creation. The work bridges philosophy, economics, and systems design, aiming to redefine the meaning of intelligence, governance, and civilization itself.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.630
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.005
Science and technology studies0.0140.001
Scholarly communication0.0040.001
Open science0.0040.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0390.011

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.

Opus teacher head0.049
GPT teacher head0.339
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it