Renumber the pipeline substeps to match the paper (5-1 becomes 5a)

prompts/ and runs/ move by git mv; zero padding dropped; the
arbitration and LLM-merge rows in the cost ledger carry no new
name -- their step column reads 已廢棄 with the original name
kept in a new last column.  Archived meta.json files and past
decision-log entries keep the names they were written with.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
This commit is contained in:
2026-08-18 23:37:32 +08:00
co-authored by Claude Opus 5
parent e3cca7e538
commit 85d776da8b
83 changed files with 144 additions and 114 deletions
@@ -0,0 +1 @@
{"id": "song-444", "text": "1. 女性身體的價值大量透過男性的慾望與認可來確立,「自然美」的宣稱最終仍服務於男性凝視:「He like the Doja with the cat, yeah」、「He like it thick, he like it fat, yeah」、「He said the body unbelievable」、「And all them niggas wanna know / How long it take to pull my pants up」。\n\n2. 以「取悅並吊住男人」作為自我經營的目標,將女性主體性化約為維持男性慾望的手段:「Like to keep him wantin' more」。\n\n3. 男聲段落以命令句直接支配女性身體,將女性化約為可供取用的部位與獵物,帶有掠食意象:「Bring that ass over, Doja, bring it back, back, back」、「I'm a big dog, tryna eat the kitty cat, cat」、「Come relax, let a nigga tap」。\n\n4. 對「同意」的態度輕慢,甚至把女方的「屈服」浪漫化,模糊了性自主與拒絕的界線:「I love when you give in, I love when you don't」、「Hit me with the threesome, and sometimes you won't」。\n\n5. 以「處女的緊緻」作為對女性身體的讚美標準,複製處女情結與以陰道狀態評價女性的物化邏輯:「Juicy and it's tighter than a virgin, like Madonna say」。\n\n6. 一面標榜「天然美」,一面貶抑橘皮組織,仍在複製排他性的身體標準,對不符合此標準的女性身體構成羞辱:「That natural beauty, beauty」對照「I don't buy it with the cellulite」。\n\n7. 將女性的身體特徵與「不可信任」的性格刻板印象掛鉤:「Can't trust a big butt and a gemini-i-i-i」。\n\n8. 使用貶抑女性的字眼「bitches」指稱其他女性,並以男性守則的口吻轉述,強化厭女語彙的流通:「You told me: Don't fuck with no bitches, you know」。\n\n9. 橋段反覆將女性拆解為臀、腿等可供男性「食用」的部位,是典型的身體碎片化物化書寫:「Need the rump and need the thighs, he eat that / Eat that up, and in the night, he seek that」。", "stop_reason": "end_turn", "usage": {"cache_creation": {"ephemeral_1h_input_tokens": 0, "ephemeral_5m_input_tokens": 0}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 0, "inference_geo": "global", "input_tokens": 1852, "output_tokens": 1557, "output_tokens_details": {"thinking_tokens": 785}, "service_tier": "batch"}}