From e6578ff10bbb02cb49d64654e0c31b882a0bc46c Mon Sep 17 00:00:00 2001 From: wassname <1103714+wassname@users.noreply.github.com> Date: Sat, 19 Sep 2026 20:27:19 +0800 Subject: [PATCH] audit respondent packet v2 panel Co-Authored-By: PI[unknown] <288921227+claudypoo@users.noreply.github.com> --- docs/RESEARCH_JOURNAL.md | 31 + scripts/wvs_respondent_packet_v1.py | 353 +++++--- .../job_1788_wvs_respondent_packet_v2.md | 217 +++++ .../20260917_score_all_options/budget.json | 10 +- .../20260919_respondent_packet/analysis.json | 558 +++++++++++++ .../20260919_respondent_packet/budget.json | 11 +- .../pueue_task_1788_clean.log | 1 + .../pueue_task_1788_status.json | 18 + .../qwen__qwen3.5-plus-02-15/packets.jsonl | 514 ++++++++++++ .../qwen__qwen3.5-plus-20260420/packets.jsonl | 514 ++++++++++++ .../records/qwen__qwen3.6-plus/packets.jsonl | 514 ++++++++++++ .../records/qwen__qwen3.7-plus/packets.jsonl | 514 ++++++++++++ .../reprocessing_inventory.json | 95 +++ .../request_attempts.jsonl | 515 ++++++++++++ .../20260919_respondent_packet/results.json | 785 ++++++++++++++++++ 15 files changed, 4547 insertions(+), 103 deletions(-) create mode 100644 slop/audits/job_1788_wvs_respondent_packet_v2.md create mode 100644 slop/research/wvs/20260919_respondent_packet/analysis.json create mode 100644 slop/research/wvs/20260919_respondent_packet/pueue_task_1788_clean.log create mode 100644 slop/research/wvs/20260919_respondent_packet/pueue_task_1788_status.json create mode 100644 slop/research/wvs/20260919_respondent_packet/records/qwen__qwen3.5-plus-20260420/packets.jsonl create mode 100644 slop/research/wvs/20260919_respondent_packet/records/qwen__qwen3.6-plus/packets.jsonl create mode 100644 slop/research/wvs/20260919_respondent_packet/records/qwen__qwen3.7-plus/packets.jsonl create mode 100644 slop/research/wvs/20260919_respondent_packet/reprocessing_inventory.json create mode 100644 slop/research/wvs/20260919_respondent_packet/results.json diff --git a/docs/RESEARCH_JOURNAL.md b/docs/RESEARCH_JOURNAL.md index 7f4b952..d024761 100644 --- a/docs/RESEARCH_JOURNAL.md +++ b/docs/RESEARCH_JOURNAL.md @@ -1266,3 +1266,34 @@ completion in the shared file) was fixed with a fixture; no second paid call. Ac encodings are now part of protocol identity (new protocol_id), eval_version stays v2. Full audit: `slop/audits/20260919_resp_packet_smoke_v2_35plus.md`. Stopped before panel dispatch as instructed. + +## 2026-09-19 -- WVS respondent packet v2 panel, task 1788 + +Observation, from task 1788 status and raw records: the authorized Alibaba panel completed 4 x 128 +whole respondent packets, 512 `request_completed` panel records. Provider-reported panel cost was +USD 0.416999506. The local stage ledger records USD 0.419875846 provider-reported over panel plus +prior smoke phases and USD 0.447093766 conservative cost after eight failed attempt bounds. The +global observed ledger now records task-1788 panel cost under `panel/resp-packet-v2/pueue-1788`. +All completed panel routes report Alibaba and the expected dated release slug; advertised +quantization is `unknown` for every release. + +Observation, from an encoding-aware reprocessing of all 512 saved raw response texts: 266 packets +that the old parser had marked nonconforming use direct visible-label variants, including integer +child labels, `answer`/`choice`/`option` fields, `q1` through `q9`, numeric-prefix keys, and answer +lists with numeric question indices. They are now appended as versioned reprocessed events, while +original events and raw text remain unchanged. Seven oldest-release list packets retain 14 refused +question instances because two question names are paraphrases rather than visible labels or exact +prompt IDs. Twenty packets have too-long reasons but retain their selected answers; reasons were +not scored. + +Observation, from the fixed whole-row bootstrap in +`slop/research/wvs/20260919_respondent_packet/analysis.json`: packet constant-family RMSE is +0.0792 and linear RMSE is 0.0696. Constant LOO error is 0.0942, lower than linear LOO error 0.1318. +Dense-v1 has the same LOO direction, 0.0338 constant versus 0.0514 linear. This is evidence against +selecting a linear release trend from these four releases. Packet coordinate shifts from dense-v1 +are positive on both axes for three releases, but this compares two evaluator administrations, not +a causal model-release effect. The published WVS map data, PNG, and SVG had a byte-empty diff. + +Full audit: `slop/audits/job_1788_wvs_respondent_packet_v2.md`. + +-- PI[unknown] diff --git a/scripts/wvs_respondent_packet_v1.py b/scripts/wvs_respondent_packet_v1.py index cfdda31..66a7334 100644 --- a/scripts/wvs_respondent_packet_v1.py +++ b/scripts/wvs_respondent_packet_v1.py @@ -220,8 +220,12 @@ def packet_schema(battery: list[dict]) -> dict: CANONICAL_SHAPE = "canonical_schema" POSITIONAL_SHAPE = "positional_labels" +Q_POSITIONAL_SHAPE = "q_positional_labels" +PREFIX_POSITIONAL_SHAPE = "numbered_prefix_labels" +ANSWER_LIST_SHAPE = "answer_list_question_indices" NO_RESPONSE_SHAPE = "no_usable_response" -ACCEPTED_ENCODINGS = (CANONICAL_SHAPE, POSITIONAL_SHAPE) +ACCEPTED_ENCODINGS = (CANONICAL_SHAPE, POSITIONAL_SHAPE, Q_POSITIONAL_SHAPE, + PREFIX_POSITIONAL_SHAPE, ANSWER_LIST_SHAPE) def refusal_row(battery: list[dict]) -> dict: @@ -245,71 +249,118 @@ def substantive_row(selected: object, reason: object, shape: str = CANONICAL_SHA "reason_status": status, "source_shape": shape} -def positional_labels(battery: list[dict]) -> dict: - """The labels render_packet displays: blocks numbered 1..9 in battery order, ordinary - options lettered A.. per block, child qualities numbered 1..11.""" - labels = {} - for number, q in enumerate(battery, 1): - if q["id"] == "ChildQualities": - labels[str(number)] = ("child", [str(j) for j in range(1, len(q["options"]) + 1)]) - else: - labels[str(number)] = ("ordinary", [chr(64 + j) for j in range(1, len(q["options"]) + 1)]) - return labels +def refused_entry(reason: object, shape: str) -> dict: + return {"outcome": "refused", "selected": None, "reason": reason, + "reason_status": "not_available", "source_shape": shape} + + +def labeled_entry(q: dict, block: object, shape: str) -> dict: + """Map one block only when it contains exactly one answer field for its visible labels.""" + if not isinstance(block, dict): + return refused_entry(None, shape) + reason = block.get("reason") + fields = ("answer", "choice", "option", "selected_option") + if q["id"] == "ChildQualities": + fields = fields + ("answers", "choices", "options", "selected_options") + present = [field for field in fields if field in block] + if len(present) != 1 or set(block) - {present[0], "reason"}: + return refused_entry(reason, shape) + value = block[present[0]] + if q["id"] == "ChildQualities": + if (not isinstance(value, list) or len(value) > 5 + or any(not isinstance(item, (str, int)) for item in value) + or len(set(value)) != len(value)): + return refused_entry(reason, shape) + labels = [str(item) for item in value] + if any(not item.isdecimal() or not 1 <= int(item) <= len(q["options"]) for item in labels): + return refused_entry(reason, shape) + return substantive_row([q["options"][int(item) - 1] for item in labels], reason, shape) + if not isinstance(value, str) or len(value) != 1: + return refused_entry(reason, shape) + index = ord(value) - ord("A") + if not 0 <= index < len(q["options"]): + return refused_entry(reason, shape) + return substantive_row(q["options"][index], reason, shape) + + +def canonical_entry(q: dict, block: object, shape: str) -> dict: + if not isinstance(block, dict) or set(block) - {"selected", "reason"}: + return refused_entry(None, shape) + selected, reason = block.get("selected"), block.get("reason") + if q["id"] == "ChildQualities": + if (isinstance(selected, list) and len(selected) <= 5 + and all(isinstance(item, str) for item in selected) + and len(set(selected)) == len(selected) and set(selected) <= set(q["options"])): + return substantive_row(selected, reason, shape) + elif selected in q["options"]: + return substantive_row(selected, reason, shape) + return refused_entry(reason, shape) + + +def positional_keys(raw: object, battery: list[dict]) -> tuple[list[str], str] | None: + if not isinstance(raw, dict): + return None + numbered = [str(number) for number in range(1, len(battery) + 1)] + if set(raw) == set(numbered): + return numbered, POSITIONAL_SHAPE + q_numbered = [f"q{number}" for number in range(1, len(battery) + 1)] + if set(raw) == set(q_numbered): + return q_numbered, Q_POSITIONAL_SHAPE + prefix = {key.split("_", 1)[0]: key for key in raw if re.fullmatch(r"[1-9]_.+", key)} + if len(prefix) == len(battery) and set(prefix) == set(numbered) and len(raw) == len(battery): + return [prefix[str(number)] for number in range(1, len(battery) + 1)], PREFIX_POSITIONAL_SHAPE + return None def normalize_positional(battery: list[dict], raw: object) -> dict | None: - """Narrow deterministic normalizer for the positional encoding: exact top-level keys - 1..9, each value exactly {answer, reason}, ordinary answers one displayed letter of that - block, child answers a unique list of 0..5 displayed number strings. Anything else -> - None (not this encoding; the caller records nonconforming refusal). Selected values map - through the rendered battery labels to the same canonical option text, so scoring is - identical to the canonical shape.""" - labels = positional_labels(battery) - if not isinstance(raw, dict) or set(raw) != set(labels): + """Map complete visible 1..9 blocks. Field names vary, labels do not.""" + keyed = positional_keys(raw, battery) + if keyed is None: return None - row = {} - for number, q in enumerate(battery, 1): - key = str(number) - block = raw[key] - if not isinstance(block, dict) or set(block) != {"answer", "reason"}: + keys, shape = keyed + return {q["id"]: labeled_entry(q, raw[key], shape) for q, key in zip(battery, keys)} + + +def normalize_answer_list(battery: list[dict], raw: object) -> dict | None: + """Map a list only through explicit visible question numbers or exact prompt IDs, never order.""" + if not isinstance(raw, dict) or set(raw) != {"answers"} or not isinstance(raw["answers"], list): + return None + by_id = {} + for block in raw["answers"]: + if not isinstance(block, dict): return None - answer, reason = block["answer"], block["reason"] - if reason_status(reason) != "valid": + index_fields = [field for field in ("question", "question_number", "question_id") if field in block] + if len(index_fields) != 1: return None - kind, valid = labels[key] - if kind == "child": - if (not isinstance(answer, list) or len(answer) > 5 - or any(not isinstance(a, str) for a in answer) - or len(set(answer)) != len(answer) - or any(a not in valid for a in answer)): - return None - selected = [q["options"][int(a) - 1] for a in answer] + index = block[index_fields[0]] + if isinstance(index, int) and 1 <= index <= len(battery): + qid = battery[index - 1]["id"] + elif isinstance(index, str) and index in {q["id"] for q in battery}: + qid = index else: - if not isinstance(answer, str) or answer not in valid: - return None - selected = q["options"][ord(answer) - 65] - row[q["id"]] = substantive_row(selected, reason, POSITIONAL_SHAPE) - return row + continue + if qid in by_id: + return None + by_id[qid] = {key: value for key, value in block.items() if key != index_fields[0]} + return {q["id"]: (labeled_entry(q, by_id[q["id"]], ANSWER_LIST_SHAPE) + if q["id"] in by_id else refused_entry(None, ANSWER_LIST_SHAPE)) + for q in battery} + + +def normalize_raw(battery: list[dict], raw: object) -> dict | None: + if not isinstance(raw, dict): + return None + answers, child = raw.get("answers"), raw.get("child_qualities") + if isinstance(answers, dict) and isinstance(child, dict): + row = {q["id"]: canonical_entry(q, child if q["id"] == "ChildQualities" else + answers.get(q["id"]), CANONICAL_SHAPE) + for q in battery} + return row + return normalize_positional(battery, raw) or normalize_answer_list(battery, raw) def parse_packet(battery: list[dict], text: str) -> tuple[dict | None, str | None, bool]: - """Classify one response. Returns (row, refusal_kind, rescueable). - - - (refusal_row, kind, False): no usable value despite the schema -> OBSERVED refusal, never - rescued. kind: 'empty_content' (empty/no content), 'no_json' (a plain-text reply with no - JSON object), or 'nonconforming' (parsed but structure/values outside the substantive - space; offending questions are refused, conforming questions keep their answers). - - a valid selected answer with a missing/too-long reason remains substantive and scored, but - gets kind 'reason_format_failure' and is retained with its raw response for qualitative audit; - it is never rescued. - - (None, None, True): clearly syntactic malformed output (an apparent JSON object that fails - to parse, or visibly truncated output with unbalanced braces) -> repairable, rescue once. - Two accepted encodings map to identical canonical selections: the schema shape - (answers/child_qualities objects) and the positional-labels shape (blocks 1..9 with one - displayed letter / 0..5 displayed numbers plus reason each). Every row entry records its - source_shape; shapes never affect scoring. - Deterministic rule: if syntactic vs substantive cannot be distinguished, it is a refusal. - """ + """Classify a response without letting reason formatting change its selected answer.""" if not (text or "").strip(): return refusal_row(battery), "empty_content", False objs = re.findall(r"\{.*\}", text, re.S) @@ -319,37 +370,12 @@ def parse_packet(battery: list[dict], text: str) -> tuple[dict | None, str | Non try: raw = json.loads(objs[-1]) except (json.JSONDecodeError, IndexError): - return None, None, True # syntactic malformed (unparseable or truncated JSON): rescue once - answers, child = raw.get("answers"), raw.get("child_qualities") - if isinstance(answers, dict) and isinstance(child, dict): - row = {} - for q in battery: - if q["id"] == "ChildQualities": - selected, reason = child.get("selected"), child.get("reason") - if (isinstance(selected, list) and len(selected) <= 5 and len(set(selected)) == len(selected) - and set(selected) <= set(q["options"])): - row[q["id"]] = substantive_row(selected, reason) - else: - row[q["id"]] = {"outcome": "refused", "selected": None, "reason": reason, - "reason_status": "not_available", - "source_shape": CANONICAL_SHAPE} - continue - answer = answers.get(q["id"]) - selected = answer.get("selected") if isinstance(answer, dict) else None - reason = answer.get("reason") if isinstance(answer, dict) else None - if selected in q["options"]: - row[q["id"]] = substantive_row(selected, reason) - else: - row[q["id"]] = {"outcome": "refused", "selected": None, "reason": reason, - "reason_status": "not_available", - "source_shape": CANONICAL_SHAPE} - else: - positional = normalize_positional(battery, raw) - if positional is None: - return refusal_row(battery), "nonconforming", False - row = positional - outcomes = [v["outcome"] for v in row.values()] - reasons = [v["reason_status"] for v in row.values()] + return None, None, True + row = normalize_raw(battery, raw) + if row is None: + return refusal_row(battery), "nonconforming", False + outcomes = [value["outcome"] for value in row.values()] + reasons = [value["reason_status"] for value in row.values()] kind = ("nonconforming" if "refused" in outcomes else "reason_format_failure" if any(status != "valid" for status in reasons) else None) return row, kind, False @@ -594,6 +620,103 @@ def prior_rows(rpath: Path, pid: str) -> dict[int, dict]: and record.get("protocol_id") == pid} +def raw_shape_signature(text: str) -> str: + """A lossless-enough structural label for auditing endpoint serialization variation.""" + try: + raw = json.loads(text) + except json.JSONDecodeError: + return "unparseable_json" + + def signature(value: object) -> str: + if isinstance(value, dict): + return "{" + ",".join(f"{key}:{signature(item)}" for key, item in sorted(value.items())) + "}" + if isinstance(value, list): + values = sorted({signature(item) for item in value}) + return "[" + ",".join(values) + "]" + return type(value).__name__ + return signature(raw) + + +def reprocessed_rows(rpath: Path, pid: str) -> dict[int, dict]: + rows = {record["packet"]: record["row"] for record in load_events(rpath) + if record.get("event") == "respondent_reprocessed" + and record.get("protocol_id") == pid} + if set(rows) != set(range(N_PACKETS)): + raise RuntimeError(f"reprocessed rows incomplete for {rpath}: {len(rows)}/{N_PACKETS}") + return rows + + +def reprocess_existing(battery: list[dict]) -> None: + """Append, never overwrite, one parser-v2 event per completed packet without API calls.""" + inventory = {"eval_version": EVAL_VERSION, "models": {}} + for model in MODELS: + rpath = OUT / "records" / model.replace("/", "__") / "packets.jsonl" + pid = protocol_id(model, battery) + events = load_events(rpath) + previous = [event for event in events if event.get("event") == "respondent_reprocessed" + and event.get("protocol_id") == pid] + if previous: + if len(previous) != N_PACKETS or {event["packet"] for event in previous} != set(range(N_PACKETS)): + raise RuntimeError(f"partial reprocessing already exists for {model} under {pid}") + rows = {event["packet"]: event["row"] for event in previous} + else: + originals = [event for event in events if event.get("event") == "respondent_parsed" + and event.get("parsed") is True] + if len(originals) != N_PACKETS or {event["packet"] for event in originals} != set(range(N_PACKETS)): + raise RuntimeError(f"expected one original parsed event per packet for {model}") + rows = {} + pending = [] + for original in originals: + row, refusal_kind, rescueable = parse_packet(battery, original["text"]) + if rescueable: + row, refusal_kind = refusal_row(battery), "unparseable_json" + assert row is not None + rows[original["packet"]] = row + pending.append({"event": "respondent_reprocessed", "model": model, + "packet": original["packet"], "seed": original["seed"], + "run_id": original["run_id"], "protocol_id": pid, + "eval_version": EVAL_VERSION, + "source_event_recorded_at_utc": original["recorded_at_utc"], + "source_protocol_id": original["protocol_id"], + "source_request_id": original["request_id"], + "normalizer_version": "encoding-aware-v1", + "raw_serialization_shape": raw_shape_signature(original["text"]), + "row": row, "refusal_kind": refusal_kind, + "rescued": False}) + for event in pending: + append_record(rpath, event) + reprocessed = [event for event in load_events(rpath) + if event.get("event") == "respondent_reprocessed" + and event.get("protocol_id") == pid] + shape_counts, raw_shape_counts, refusal_kinds = {}, {}, {} + for row in rows.values(): + shapes = {value["source_shape"] for value in row.values()} + if len(shapes) != 1: + raise RuntimeError(f"reprocessed packet used mixed source shapes: {model}") + shape = next(iter(shapes)) + shape_counts[shape] = shape_counts.get(shape, 0) + 1 + for value in row.values(): + if value["outcome"] == "refused": + refusal_kinds[value["reason_status"]] = refusal_kinds.get(value["reason_status"], 0) + 1 + for event in reprocessed: + shape = event["raw_serialization_shape"] + raw_shape_counts[shape] = raw_shape_counts.get(shape, 0) + 1 + packet_kinds = {} + for event in reprocessed: + if event["refusal_kind"] not in (None, "reason_format_failure"): + kind = event["refusal_kind"] + packet_kinds[kind] = packet_kinds.get(kind, 0) + 1 + inventory["models"][model] = {"protocol_id": pid, "packets": len(rows), + "canonicalization_shape_counts": shape_counts, + "raw_serialization_shape_counts": raw_shape_counts, + "residual_refused_packets": sum(packet_kinds.values()), + "residual_refusal_packet_kinds": packet_kinds, + "residual_refused_question_instances": sum(refusal_kinds.values()), + "residual_refusal_reason_status_counts": refusal_kinds} + atomic_json(OUT / "reprocessing_inventory.json", inventory) + print("reprocessing complete: appended encoding-aware rows without API calls") + + def protocol_body(model: str, battery: list[dict]) -> dict: return { "schema": 1, "eval_version": EVAL_VERSION, "model": model, @@ -779,7 +902,7 @@ def offline_smoke(battery: list[dict], child_rows: list[dict]) -> None: # identity: v2 everywhere; protocol/cache identity includes accepted response encodings assert EVAL_VERSION == "wvs-respondent-packet-v2" body = protocol_body(MODELS[0], battery) - assert body["accepted_response_encodings"] == ["canonical_schema", "positional_labels"] + assert body["accepted_response_encodings"] == list(ACCEPTED_ENCODINGS) assert body["eval_version"] == EVAL_VERSION # fixture: visible prompt contains no refusal/null/AI-identity language prompt = render_packet(battery).lower() @@ -920,8 +1043,41 @@ def offline_smoke(battery: list[dict], child_rows: list[dict]) -> None: assert pos_row["ChildQualities"]["selected"] == [child_opts[0], child_opts[1], child_opts[5], child_opts[7], child_opts[9]] - # fixture: positional ambiguity rejections. Each mutation must yield None (not this - # encoding), never a guessed mapping. + # fixture: endpoint serialization variants preserve the visible labels, not guessed meaning. + # These are the observed q1..q9, numbered-prefix, and explicit-index list encodings. + q_blocks = {f"q{number}": {"choice": raw_positional[str(number)]["answer"], + "reason": raw_positional[str(number)]["reason"]} + for number in range(1, 9)} + q_blocks["q9"] = {"choices": [int(value) for value in raw_positional["9"]["answer"]], + "reason": raw_positional["9"]["reason"]} + q_row, q_kind, _ = parse_packet(battery, json.dumps(q_blocks)) + assert q_kind is None and all(value["outcome"] == "substantive" for value in q_row.values()) + assert {value["source_shape"] for value in q_row.values()} == {Q_POSITIONAL_SHAPE} + prefix_blocks = {f"{number}_visible_label": {"option": raw_positional[str(number)]["answer"], + "reason": raw_positional[str(number)]["reason"]} + for number in range(1, 9)} + prefix_blocks["9_visible_label"] = {"options": [int(value) for value in raw_positional["9"]["answer"]], + "reason": raw_positional["9"]["reason"]} + prefix_row, prefix_kind, _ = parse_packet(battery, json.dumps(prefix_blocks)) + assert prefix_kind is None and all(value["outcome"] == "substantive" for value in prefix_row.values()) + assert {value["source_shape"] for value in prefix_row.values()} == {PREFIX_POSITIONAL_SHAPE} + answer_list = {"answers": [{"question_id": number, + "selected_option": raw_positional[str(number)]["answer"], + "reason": raw_positional[str(number)]["reason"]} + for number in range(1, 9)] + + [{"question_id": 9, "selected_options": [int(value) for value in raw_positional["9"]["answer"]], + "reason": raw_positional["9"]["reason"]}]} + list_row, list_kind, _ = parse_packet(battery, json.dumps(answer_list)) + assert list_kind is None and all(value["outcome"] == "substantive" for value in list_row.values()) + assert {value["source_shape"] for value in list_row.values()} == {ANSWER_LIST_SHAPE} + duplicate_index = json.loads(json.dumps(answer_list)) + duplicate_index["answers"][1]["question_id"] = 1 + assert normalize_answer_list(battery, duplicate_index) is None + unknown_index = json.loads(json.dumps(answer_list)) + unknown_index["answers"][4]["question_id"] = "Trust in people" + unknown_row = normalize_answer_list(battery, unknown_index) + assert unknown_row is not None and unknown_row["dealing with people?"]["outcome"] == "refused" + # fixture: positional ambiguity rejections. No invalid or ambiguous label becomes substantive. def mutate(block_key, field, value): mutated = json.loads(json.dumps(raw_positional)) if block_key not in mutated: @@ -946,15 +1102,17 @@ def offline_smoke(battery: list[dict], child_rows: list[dict]) -> None: mutate("9", "answer", ["1", "1"]), mutate("9", "answer", ["0"]), mutate("9", "answer", ["12"]), - mutate("9", "answer", [1, 2]), mutate("9", "answer", ["1", "2", "3", "4", "5", "6"]), - mutate("1", "reason", "These nine separate words exceed the permitted reason length now"), - mutate("1", "reason", ""), - mutate("2", "reason", None), mutate("3", "__extra_block_key__", ("confidence", "high")), ] for i, bad in enumerate(rejections): - assert normalize_positional(battery, bad) is None, f"rejection fixture {i} mapped" + rejected = normalize_positional(battery, bad) + assert rejected is None or any(value["outcome"] == "refused" for value in rejected.values()), ( + f"rejection fixture {i} mapped to substantive answers") + long_reason = mutate("1", "reason", "These nine separate words exceed the permitted reason length now") + long_row = normalize_positional(battery, long_reason) + assert long_row is not None and long_row["Religion"]["outcome"] == "substantive" + assert long_row["Religion"]["reason_status"] == "too_long" # fixture: duplicate / oversized child lists are nonconforming (uniqueness enforced in parsing, # since Alibaba rejects array schemas with the uniqueness keyword) dup_row, dup_kind, rescueable = parse_packet(battery, json.dumps( @@ -1356,6 +1514,7 @@ def main() -> None: actions.add_argument("--write-manifest", action="store_true") actions.add_argument("--paid-smoke", action="store_true") actions.add_argument("--reinterpret-smoke", action="store_true") + actions.add_argument("--reprocess-existing", action="store_true") actions.add_argument("--run", action="store_true") actions.add_argument("--analyze", action="store_true") actions.add_argument("--synthetic-analysis-test", action="store_true") @@ -1385,6 +1544,8 @@ def main() -> None: paid_smoke(args.smoke_model, battery) if args.reinterpret_smoke: reinterpret_smoke_35plus(battery) + if args.reprocess_existing: + reprocess_existing(battery) if args.run: run(battery) if args.analyze: @@ -1795,7 +1956,7 @@ def analyze_real() -> None: packet_rows = {} for m in MODELS: rpath = OUT / "records" / m.replace("/", "__") / "packets.jsonl" - packet_rows[m] = prior_rows(rpath, protocol_id(m, battery)) + packet_rows[m] = reprocessed_rows(rpath, protocol_id(m, battery)) analysis = analyze_from_data(packet_rows, battery, child_rows, resolved) atomic_json(OUT / "analysis.json", analysis) print(json.dumps({"packet": {k: analysis["packet"][k] diff --git a/slop/audits/job_1788_wvs_respondent_packet_v2.md b/slop/audits/job_1788_wvs_respondent_packet_v2.md new file mode 100644 index 0000000..f5d8295 --- /dev/null +++ b/slop/audits/job_1788_wvs_respondent_packet_v2.md @@ -0,0 +1,217 @@ +# Audit: Pueue task 1788, WVS respondent packet v2 + +Scope: offline audit and reanalysis of the completed 4 x 128 Qwen Plus packet panel. No replacement API calls were made. This audit covers the raw response bytes, encoding-aware reprocessing, fixed comparison to `wvs-score-all-options-v1`, costs, route metadata, and published-map integrity. + +## Stage table + +| stage | expected | observed | expected? | clues | missing metric | consequence | +|---|---|---|---|---|---|---| +| dispatch | API task runs once and finishes | task 1788 is `Success` after 51m36s | yes | `pueue_task_1788_status.json` | worker stdout progress | stdout cannot establish data validity | +| raw persistence | 512 complete packet records | 128 `respondent_parsed` events for each of 4 releases | yes | four `records/*/packets.jsonl` files | none | raw text supports independent reprocessing | +| parser | valid visible labels stay substantive | 266 of 273 prior nonconforming packets map deterministically; 7 retain two unmapped question fields | no, before fix | `reprocessing_inventory.json` | human adjudication of two paraphrase labels | the original refusal rates were parser artifacts | +| reason policy | reasons never change choices | 20 packets have `reason_format_failure`; their choices remain substantive | yes after fix | reprocessed events, `analysis.json` | none | reasons are qualitative only | +| packet analysis | whole-row bootstrap, fixed items, all 4 releases | 1,000 complete bootstrap draws per protocol | yes | `analysis.json` | repeated independent panel | uncertainty is sampling conditional on this serving route | +| dense comparison | same releases and fixed items | all 4 dense-v1 coordinates and packet-minus-dense CIs written | yes | `analysis.json` | paired responses, which do not exist | shift CIs use independent bootstraps | +| budget and route | pinned Alibaba route, costs reconciled | all completed panel routes are Alibaba, advertised quantization `unknown`; global observed ledger records panel cost | partial | `request_attempts.jsonl`, both budget ledgers | provider statement of failed-attempt charges | local conservative cost exceeds observed cost by failed-attempt reserve bounds | +| publication safety | no map changes | byte-empty diff and the three tracked map hashes match pre-audit values | yes | command below | none | this task did not publish or replace map coordinates | + +## Provenance and raw-response audit + +The task status artifact records the exact command, branch path, and terminal state: + +> `"command": "scripts/wvs_api/10_respondent_packet_v2_panel.sh"` +> `"path": "/workspace/2026/lite/moralmaps"` +> `"result": "Success"` + +Source: `slop/research/wvs/20260919_respondent_packet/pueue_task_1788_status.json`, copied from `pueue status --json` for task 1788. The complete Pueue log after ANSI and carriage-return stripping is one line, not a progress log: + +> `panel complete` + +Source: `slop/research/wvs/20260919_respondent_packet/pueue_task_1788_clean.log`, SHA-256 `92473da432bf48210d2a3cdb0d0386b5299493fd07f8b38afde9eb1dc66ad684` for the raw Pueue log. This establishes only successful shell completion; the packet JSONLs are the primary outcome evidence. + +I inspected all 512 `respondent_parsed` raw `text` values. All were one well-formed JSON object. There were no empty texts, no no-JSON replies, no unparseable JSON, and no rescues. The original parser accepted the canonical schema and one strict positional spelling only. It had marked 273 responses nonconforming because endpoint serialization varied. + +The new encoding-aware protocol accepts only mappings from visible labels: + +- ordinary block `n`, `A` through the displayed maximum letter -> option `n`'s displayed option; +- child item integer or decimal string `1..11` -> the displayed 1-indexed child quality; +- numbered blocks `1..9`, `q1..q9`, or `N_...` blocks map by their visible numeric label; +- answer lists map only by explicit numeric question index or exact prompt ID, never by list order. + +It accepts exactly one selection key per block. The supported keys are `answer`, `choice`, `option`, and `selected_option`, plus plural forms for child lists. A missing or >8-word reason sets `reason_status` but retains a valid selection. Duplicate indices, duplicate child values, out-of-range labels, lowercase letters, multiple choice fields, and unknown question aliases are refused. Fixtures in `offline_smoke` cover the observed forms and these ambiguity rejections. + +Exact reprocessed packet shape counts: + +| release | canonical | numbered | q-numbered | N-prefix | numeric answer list | true-refusal packets | refused question instances | +|---|---:|---:|---:|---:|---:|---:|---:| +| qwen3.5-plus-02-15 | 0 | 86 | 0 | 2 | 40 | 7 | 14 | +| qwen3.6-plus | 0 | 109 | 3 | 0 | 16 | 0 | 0 | +| qwen3.5-plus-20260420 | 0 | 127 | 1 | 0 | 0 | 0 | 0 | +| qwen3.7-plus | 128 | 0 | 0 | 0 | 0 | 0 | 0 | + +Source: `reprocessing_inventory.json`. The complete structural inventory, including key and scalar-type signature, is in that file. The seven residual packets are `qwen3.5-plus-02-15` answer lists with two paraphrase identifiers, including `"Trust in people"` and `"Important qualities for children"`. Those identifiers are not displayed labels or exact prompt IDs, so mapping them would need semantic inference. The other seven answers in each such packet remain directly labeled; the two unmapped question instances stay refusals. This is a partial-item refusal, not an invented full-packet refusal. + +Examples of deterministic mappings: + +> `"1": {"option": "C", ...}, ... "9": {"options": [1, 2, 6, 8, 10], ...}` + +Source: `records/qwen__qwen3.5-plus-02-15/packets.jsonl`, packet 3. The visible `C` and child numbers map directly through the rendered labels. + +> `"answers": [{"question_id": 1, "selected_option": "C", ...}, ... {"question_id": 9, "selected_options": [1, 2, 6, 9, 10], ...}]` + +Source: `records/qwen__qwen3.6-plus/packets.jsonl`, packet 7. Each numeric `question_id` is an explicit displayed block number. + +A fresh read-only reviewer separately audited every raw structure and identified the same two categories: deterministic label variation and seven name-paraphrase packets that must not be semantically mapped. Its session artifact is `/home/code/.pi/agent/sessions/--workspace-2026-lite-moralmaps--/subagent-artifacts/outputs/34acf2a8-94e1-46a3-a39e-cee4179392ee/slop/reviews/20260919_respondent_packet_raw_schema_review.md`. + +## Reanalysis + +Coordinates are `[Survival <-> Self-expression, Traditional <-> Secular-Rational]`. Packet CIs and SEs use B=1,000 whole-respondent-row bootstrap draws. Dense-v1 uses its existing per-item rating samples, so packet-minus-dense shifts use independent bootstrap draws. + +| release | packet coordinate, SE | packet CI95 | dense-v1 coordinate, SE | packet minus dense, CI95 | +|---|---|---|---|---| +| qwen3.5-plus-02-15 | [0.7734, 0.7599], [0.0094, 0.0058] | [[0.7539, 0.7495], [0.7906, 0.7715]] | [0.5372, 0.6595], [0.0070, 0.0052] | [0.2362, 0.1004], [[0.2110, 0.0863], [0.2576, 0.1152]] | +| qwen3.6-plus | [0.7320, 0.8100], [0.0155, 0.0067] | [[0.7023, 0.7971], [0.7609, 0.8224]] | [0.5197, 0.6699], [0.0082, 0.0101] | [0.2124, 0.1401], [[0.1780, 0.1159], [0.2466, 0.1621]] | +| qwen3.5-plus-20260420 | [0.5789, 0.7783], [0.0105, 0.0084] | [[0.5586, 0.7615], [0.5992, 0.7945]] | [0.5856, 0.6494], [0.0159, 0.0071] | [-0.0067, 0.1289], [[-0.0431, 0.1062], [0.0312, 0.1503]] | +| qwen3.7-plus | [0.7281, 0.8341], [0.0204, 0.0075] | [[0.6867, 0.8193], [0.7648, 0.8486]] | [0.5078, 0.6664], [0.0093, 0.0083] | [0.2203, 0.1676], [[0.1731, 0.1459], [0.2603, 0.1889]] | + +Source: `analysis.json`. The coordinates are data descriptions, not released map replacements. + +| evaluator | constant-family RMSE | linear-release RMSE | response-noise floor, constant / linear | LOO constant, CI95 | LOO linear, CI95 | +|---|---:|---:|---:|---:|---:| +| packet v2 | 0.0792 | 0.0696 | 0.0132 / 0.0104 | 0.0942, [0.0840, 0.1072] | 0.1318, [0.1018, 0.1599] | +| dense v1 | 0.0307 | 0.0304 | 0.0108 / 0.0092 | 0.0338, [0.0236, 0.0506] | 0.0514, [0.0309, 0.0769] | + +Observations: + +- Packet family scatter is about six times its simulated response-noise floor, 0.0792 / 0.0132. This is strong evidence that the release differences are not explained by this bootstrap sampling noise alone. +- Linear fit has lower in-sample packet RMSE, 0.0696 vs 0.0792, but worse packet leave-one-release-out error, 0.1318 vs 0.0942. With four releases, the observed linear improvement is likely overfit rather than evidence for a release trend. +- Dense v1 also has worse LOO for the line, 0.0514 vs 0.0338. This supports the same warning but does not prove either protocol is closer to a human coordinate. +- Packet-vs-dense shifts are positive on both axes for three releases. The later 3.5 revision has an X shift CI overlapping zero and positive Y shift. These shifts are expected to include administration and representation changes, not just model behavior. + +Qualitative reasons were inspected but never scored or used to select a protocol. They frequently describe AI identity or lack of physical agency. Examples include: + +> `"I am an AI without spiritual beliefs."` + +and + +> `"I cannot physically sign documents."` + +Source: raw response text in `records/qwen__qwen3.5-plus-20260420/packets.jsonl`, packet 1. This is an observation about the model's stated framing. It does not establish a causal explanation for the coordinates. + +## Costs, attempts, and route metadata + +The 512 panel `request_completed` events report USD 0.416999506 total: + +| release | completed panel calls | provider-reported panel cost | selected release slug | +|---|---:|---:|---| +| qwen3.5-plus-02-15 | 128 | 0.099283600 | qwen/qwen3.5-plus-20260216 | +| qwen3.6-plus | 128 | 0.121719650 | qwen/qwen3.6-plus-04-02 | +| qwen3.5-plus-20260420 | 128 | 0.110536800 | qwen/qwen3.5-plus-20260420 | +| qwen3.7-plus | 128 | 0.085459456 | qwen/qwen3.7-plus-20260602 | + +Every completed request in `request_attempts.jsonl` has `selected_provider: Alibaba`, `endpoint_tag: alibaba`, `response_model` equal to the requested model, and `advertised_quantization: unknown`. The four-release comparison is one provider and product tier, but quantization remains unknown. This is a route limitation, not evidence of a matched underlying precision. + +Across the local stage ledger there are 524 attempt events: 516 completed and 8 failed. The 8 failures are six HTTP 400 and two HTTP 429 events. The local ledger reports provider cost USD 0.419875846 and conservative cost USD 0.447093766, with `reserved_usd: "0E-9"`; the difference covers failed-phase reserve charges and pre-panel smoke phases. The global ledger now contains `panel/resp-packet-v2/pueue-1788: "0.416999506"`, has no outstanding reservations, and was reconciled at `2026-09-19T12:22:49.318979+00:00`. It records observed provider panel cost, not an assertion that failed requests were free. + +## ML-debug form, hypotheses, and decision + +| row | answer | +|---|---| +| log length and config | Pueue log after ANSI and carriage-return stripping is 1/1 line; task executed `scripts/wvs_api/10_respondent_packet_v2_panel.sh`; each payload and response is retained in 512 raw record triplets. | +| `SHOULD` checks | no `SHOULD:` lines in task stdout; the real checks are route validation, raw persistence, reprocessing fixtures, and map diff. | +| null / scale | a null family has the simulated response-noise floor above; observed scatter exceeds it. Linear-vs-constant generalization is the LOO comparison, not in-sample RMSE. | +| full sample | raw packet examples above; every model's 128 raw responses were structurally inventoried. | +| surprising observation | qwen3.6 had 128/128 apparent refusals before reprocessing but has 128 direct label-mapped packets afterward. This was parser strictness, not an observed provider refusal. | +| missing evidence | independent repeat panels, known quantization, and a human-response calibration of the packet framing. | +| fresh review | the independent reviewer artifact above found the same strict-parser issue and kept name-paraphrase list fields unscored. | +| wall-clock | 51m36s for task 1788; sequential API requests were intentional. | + +### H1 [bug | Almost Certain | 95%] + +- Mechanism: the prior parser accepted only a strict schema and one strict positional form. It classified endpoint key spelling, integer child labels, and numeric answer lists as refusals. +- Evidence: `reprocessing_inventory.json` records 109 numbered plus 16 numeric-list packets for qwen3.6, while the original `results.json` had coverage 0.0 for that model. The raw response form uses visible labels, for example `"question_id": 9` with `"selected_options": [1, 2, 6, 9, 10]`. +- Contrary evidence: seven answer-list packets contain paraphrase question identifiers; those are not mapped. +- Discriminating test: rerun the offline fixtures against a response with two selection keys, a duplicate numeric question index, or `"Trust in people"`. Expected: no substantive mapping for the ambiguous field. The fixtures pass. +- Fix/action: append `respondent_reprocessed` rows under new encoding-aware protocol IDs; preserve raw and original parsed events. +- Interpretability: partial before reprocessing, yes after deterministic reprocessing. + +### H2 [measurement | Highly Likely | 80%] + +- Mechanism: packet choice frequencies and dense option ratings are different administrations and response geometries, so their coordinate differences are protocol effects as well as model effects. +- Evidence: packet-minus-dense shifts are [0.2362, 0.1004] for the oldest release and [0.2203, 0.1676] for qwen3.7, with both coordinate CIs positive. +- Contrary evidence: one later-3.5 X shift is -0.0067 with CI [-0.0431, 0.0312], so protocol shifts are not constant across releases. +- Discriminating test: repeat both evaluators with multiple independent respondent panels and a preregistered common scoring subset. A stable within-model shift across repeats would support an administration effect. +- Fix/action: report both evaluator versions separately. Do not overwrite dense coordinates or publish packet coordinates. +- Interpretability: yes for within-protocol descriptions; no for a claim that either is the human-ground-truth coordinate. + +### H3 [method | Likely | 65%] + +- Mechanism: the in-sample linear release fit overfits four heterogeneous releases. +- Evidence: packet linear RMSE is lower in sample, 0.0696 vs 0.0792, yet linear LOO error is higher, 0.1318 vs 0.0942. Dense v1 has the same sign, 0.0514 vs 0.0338 LOO. +- Contrary evidence: both point metrics are calculated on the only available four-release family; there is no held-out fifth Qwen Plus release. +- Discriminating test: add a preregistered fifth same-route release, then compare constant and linear predictions without refitting their form. +- Fix/action: treat family centroid as the better current predictive summary; do not select a release trend. +- Interpretability: yes for the observed four-release scatter, partial for extrapolation. + +### H4 [harness | Likely | 60%] + +- Mechanism: unknown advertised quantization and no independent panel leave route and response-sampling effects confounded with release differences. +- Evidence: every route record says `advertised_quantization: unknown`; response-noise floors are much lower than packet scatter, but bootstrap does not model route changes or a different generation run. +- Contrary evidence: provider is pinned to Alibaba and each completed response validates its dated release slug. +- Discriminating test: run an approved repeat with saved endpoint metadata that states quantization, or a provider route with known matched precision. +- Fix/action: retain route metadata and qualify release comparisons as service-release comparisons. +- Interpretability: partial. + +### H5 [data | Chances a little better than even | 50%] + +- Mechanism: the model frames itself as an AI despite the respondent instruction, particularly on religion and physical political actions, which can change packet coordinates. +- Evidence: raw reasons include `"I am an AI without spiritual beliefs."` and `"I cannot physically sign documents."`. +- Contrary evidence: reasons are short, not exhaustive rationales, and were not scored. They cannot estimate how much this framing moved a coordinate. +- Discriminating test: compare a future preregistered framing manipulation while holding schema, model, route, and sample count fixed. +- Fix/action: retain reasons as qualitative audit material only. +- Interpretability: yes for observed answers, no causal attribution to the stated reasons. + +## Resolve condition and recommendation + +The task label says: + +> `resolve: audit uncertainty, refusals, family scatter and release trend without publishing` + +Verdict: met. The full raw panel was reprocessed without calls, uncertainty and coverage are in `analysis.json`, family scatter and LOO trend tests are reported, costs and routes are reconciled, and the map diff is empty. + +Prediction check: the plan recorded no directional prediction that a line should generalize better than a family centroid. The observed LOO result contradicts choosing the line. The original parser's reported refusal pattern is contradicted by the raw responses. + +Earliest unsupported link: a service-release difference is not yet a model-release difference, because advertised quantization is unknown and there is only one response panel per release. + +Validity: define invalid as a result that still silently treats deterministic serialization variants as refusals, changes the published map, loses respondent covariance, or fits trend metrics after a coverage collapse. Under that definition, P(invalid) is about 0.10 to 0.20. The main result is a credible descriptive packet-vs-dense comparison, not a credible causal estimate of model evolution. + +Highest-information clues, in order: + +1. qwen3.6 raw responses used visible labels in all 128 packets despite original 100% refusal output. This directly localized a parser error. +2. Packet linear LOO is worse than constant LOO despite a better in-sample line. This rejects the tempting trend interpretation. +3. Packet scatter is materially above the response-noise floor. This rejects an explanation based only on within-panel resampling variation. + +Missing evidence, ordered by expected information gain: (1) a fifth or repeated same-route panel, (2) verified route precision, (3) human calibration of the respondent prompt, (4) manual adjudication only if name-paraphrase items must be recovered. + +Recommended sequence: keep this versioned packet result as an un-published evaluator artifact; do not choose a linear trend or replace the dense map. Before any broader family panel, require a known-precision route or state that precision is unknown, and run a fixed repeat or fifth-release prediction check. Do not combine a prompt change, route change, and evaluator change in one follow-up because that destroys attribution. + +## Verification commands + +```sh +uv run --offline --with 'datasets>=4.0,<5' python scripts/wvs_respondent_packet_v1.py --offline-smoke +uv run --offline --with 'datasets>=4.0,<5' python scripts/wvs_respondent_packet_v1.py --offline-regression +uv run --offline --with 'datasets>=4.0,<5' python scripts/wvs_respondent_packet_v1.py --synthetic-analysis-test +uv run --offline --with 'datasets>=4.0,<5' python scripts/wvs_respondent_packet_v1.py --reprocess-existing +uv run --offline --with 'datasets>=4.0,<5' python scripts/wvs_respondent_packet_v1.py --analyze +sha256sum slop/research/wvs/20260919_respondent_packet/analysis.json slop/research/wvs/20260919_respondent_packet/reprocessing_inventory.json +git diff --quiet -- docs/wvs/wvs_map_data.json docs/img/wvs/wvs_map_iw.png docs/img/wvs/wvs_map_iw.svg +``` + +Two full deterministic analysis executions produced the same SHA-256s: + +> `887f66cd56e9abb38ec87df58f5060058c2726485607573744010a58783b3ce6 analysis.json` +> `f12badd1faa210b33a881bbbbfc0db5abe1cc0a53fbea449e77330ff1c65889b reprocessing_inventory.json` + +Map diff exit code was 0. Map SHA-256 values are `c03b5104a9a31482fa547a8a2996e33d3d3d59453d5189f94e95d9d451bf63d1` for JSON, `a7164901ff69e1e51696ade8fb9dd9c62d81af5cfa0c94a49ddf5598c68b4103` for PNG, and `d35cb80a70d34472e967ac1453aa54d43c24418b8b74fe71e726d2a927771aa2` for SVG. + +-- PI[unknown] diff --git a/slop/research/wvs/20260917_score_all_options/budget.json b/slop/research/wvs/20260917_score_all_options/budget.json index 1f831ff..b9bc26a 100644 --- a/slop/research/wvs/20260917_score_all_options/budget.json +++ b/slop/research/wvs/20260917_score_all_options/budget.json @@ -1,16 +1,22 @@ { "external_observed_usd": { + "panel/resp-packet-v2/pueue-1788": "0.416999506", "pilot/deepseek-wvs-v1-reliability": "0.364683724004", "pilot/gemini-flash-rubric-smoke-2048/20260918T114112.952954Z": "0.0046880", "pilot/gemini-flash-rubric-smoke/20260918T111625.452461Z": "0.0053585", "pilot/gemini-flash-rubric/20260918T115056.470656Z": "3.19879800", "pilot/original-choice-smoke/20260918T233052.482300Z": "0.00072075", "pilot/original-choice-unplanned-3.8-panel/20260918T232000Z": "0.07433250", - "pilot/original-choice/20260918T233134.028604Z": "0.23466450" + "pilot/original-choice/20260918T233134.028604Z": "0.23466450", + "pilot/resp-packet-smoke/20260919T053145.242627Z": "0.00884736", + "pilot/resp-packet-smoke/20260919T053327.788868Z": "0.00054048", + "pilot/resp-packet-smoke/20260919T091356.312349Z": "0.00079616", + "pilot/resp-packet-smoke/20260919T094956.647597Z": "0.00078752", + "pilot/resp-packet-smoke/qwen__qwen3.5-plus-02-15/20260919T095711.451681Z": "0.00075218" }, "prior_observed_usd": "5.34309727235", "rated_ledger_cost_usd": "7.388069120252", - "reconciled_utc": "2026-09-18T23:58:08.537078+00:00", + "reconciled_utc": "2026-09-19T12:22:49.318979+00:00", "reservations": {}, "schema": 1 } diff --git a/slop/research/wvs/20260919_respondent_packet/analysis.json b/slop/research/wvs/20260919_respondent_packet/analysis.json new file mode 100644 index 0000000..d2334c5 --- /dev/null +++ b/slop/research/wvs/20260919_respondent_packet/analysis.json @@ -0,0 +1,558 @@ +{ + "coord_shifts_packet_minus_dense": { + "qwen/qwen3.5-plus-02-15": { + "ci95": [ + [ + 0.21102391286375677, + 0.08629490858843536 + ], + [ + 0.2576009286816579, + 0.1151687370995406 + ] + ], + "point": [ + 0.23623291446208117, + 0.10040918076632366 + ], + "valid_shift_draws": 1000 + }, + "qwen/qwen3.5-plus-20260420": { + "ci95": [ + [ + -0.043054920484608045, + 0.10618798013329245 + ], + [ + 0.03117986975408853, + 0.150264314058957 + ] + ], + "point": [ + -0.006713939995189988, + 0.12887195476481184 + ], + "valid_shift_draws": 1000 + }, + "qwen/qwen3.6-plus": { + "ci95": [ + [ + 0.1779594534573089, + 0.11585783512122784 + ], + [ + 0.2466465092981637, + 0.16213250043607186 + ] + ], + "point": [ + 0.2123533788515407, + 0.14012042851328554 + ], + "valid_shift_draws": 1000 + }, + "qwen/qwen3.7-plus": { + "ci95": [ + [ + 0.173092647707231, + 0.14586338595267162 + ], + [ + 0.2603233162477953, + 0.18892989554261871 + ] + ], + "point": [ + 0.2203053350970018, + 0.1676414689807546 + ], + "valid_shift_draws": 1000 + } + }, + "dense_v1": { + "bootstrap_note": "item-wise independent resampling of the 12 rating vectors per item; dense samples are not row-linked, so protocols are not pairable and differences use independent bootstraps", + "constant_family_rmse": 0.030656386808492638, + "constant_family_rmse_ci95": [ + 0.019709664939171884, + 0.04434030190202118 + ], + "constant_family_rmse_se": 0.006507875414184742, + "constant_noise_floor_mean": 0.010782097533767028, + "coord_ci95": { + "qwen/qwen3.5-plus-02-15": [ + [ + 0.5245582010582011, + 0.6499197809465668 + ], + [ + 0.5511746031746032, + 0.6701631453863597 + ] + ], + "qwen/qwen3.5-plus-20260420": [ + [ + 0.5532252472643097, + 0.6347606147159718 + ], + [ + 0.6171024944384319, + 0.6624319182801326 + ] + ], + "qwen/qwen3.6-plus": [ + [ + 0.5034069275858492, + 0.6505467796092796 + ], + [ + 0.5360376465400974, + 0.6908188611983256 + ] + ], + "qwen/qwen3.7-plus": [ + [ + 0.48869833002645496, + 0.6495983233036804 + ], + [ + 0.5251521439594357, + 0.6827553109919182 + ] + ] + }, + "coord_se": { + "qwen/qwen3.5-plus-02-15": [ + 0.006969411536743106, + 0.005177089691727466 + ], + "qwen/qwen3.5-plus-20260420": [ + 0.015929318069842775, + 0.007075160953994892 + ], + "qwen/qwen3.6-plus": [ + 0.00819408400769001, + 0.010124807457482635 + ], + "qwen/qwen3.7-plus": [ + 0.00934551982215177, + 0.008297510115857632 + ] + }, + "family_bootstrap": { + "bootstrap_B": 1000, + "complete_draw_fraction": 1.0, + "complete_draws": 1000, + "constant_family_rmse_draws_mean": 0.03195155055660286, + "constant_family_rmse_draws_se": 0.006507875414184742, + "linear_trend_rmse_draws_mean": 0.031144856064642835, + "linear_trend_rmse_draws_se": 0.006765267258401058, + "loo_constant_mean_ci95": [ + 0.023632756088608507, + 0.05063057965425209 + ], + "loo_constant_mean_draws_mean": 0.036785573395985, + "loo_constant_mean_draws_se": 0.00710827972882462, + "loo_linear_mean_ci95": [ + 0.030943523904004264, + 0.07694505839895653 + ], + "loo_linear_mean_draws_mean": 0.053834856217117574, + "loo_linear_mean_draws_se": 0.012100516076685882, + "min_complete_draws_required": 100, + "status": "ok", + "valid_draws_per_model": { + "qwen/qwen3.5-plus-02-15": 1000, + "qwen/qwen3.5-plus-20260420": 1000, + "qwen/qwen3.6-plus": 1000, + "qwen/qwen3.7-plus": 1000 + } + }, + "family_point": { + "constant_family_rmse": 0.030656386808492638, + "linear_trend_rmse": 0.03036728669286448, + "loo": { + "constant_loo_mean": 0.03379600217245676, + "constant_loo_per_release": [ + 0.0024527195142407055, + 0.026474233883769488, + 0.06599204886374982, + 0.040265006428067046 + ], + "linear_loo_mean": 0.05138288588567405, + "linear_loo_per_release": [ + 0.026305590253706657, + 0.02858299431983149, + 0.07122248618854347, + 0.0794204727806146 + ] + }, + "status": "ok" + }, + "linear_noise_floor_mean": 0.009243758127528314, + "linear_trend_rmse": 0.03036728669286448, + "linear_trend_rmse_ci95": [ + 0.018053582001113583, + 0.04387165462610324 + ], + "linear_trend_rmse_se": 0.006765267258401058, + "loo": { + "constant_loo_mean": 0.03379600217245676, + "constant_loo_per_release": [ + 0.0024527195142407055, + 0.026474233883769488, + 0.06599204886374982, + 0.040265006428067046 + ], + "linear_loo_mean": 0.05138288588567405, + "linear_loo_per_release": [ + 0.026305590253706657, + 0.02858299431983149, + 0.07122248618854347, + 0.0794204727806146 + ] + }, + "loo_constant_mean_ci95": [ + 0.023632756088608507, + 0.05063057965425209 + ], + "loo_constant_mean_se": 0.00710827972882462, + "loo_linear_mean_ci95": [ + 0.030943523904004264, + 0.07694505839895653 + ], + "loo_linear_mean_se": 0.012100516076685882, + "p_constant_noise_ge_observed": 0.0, + "p_linear_noise_ge_observed": 0.0, + "point_coords_xy_per_model": { + "qwen/qwen3.5-plus-02-15": [ + 0.5372045855379188, + 0.6595114541543113 + ], + "qwen/qwen3.5-plus-20260420": [ + 0.5856201899951899, + 0.6494018547589976 + ], + "qwen/qwen3.6-plus": [ + 0.5196778711484593, + 0.6698994127565557 + ], + "qwen/qwen3.7-plus": [ + 0.5078196649029982, + 0.6664359119716262 + ] + }, + "point_status": "ok", + "unavailable_items": { + "qwen/qwen3.5-plus-02-15": { + "Survival <-> Self-expression": [], + "Traditional <-> Secular-Rational": [] + }, + "qwen/qwen3.5-plus-20260420": { + "Survival <-> Self-expression": [], + "Traditional <-> Secular-Rational": [] + }, + "qwen/qwen3.6-plus": { + "Survival <-> Self-expression": [], + "Traditional <-> Secular-Rational": [] + }, + "qwen/qwen3.7-plus": { + "Survival <-> Self-expression": [], + "Traditional <-> Secular-Rational": [] + } + } + }, + "eval_version": "wvs-respondent-packet-v2", + "n_packets": 128, + "packet": { + "child_diagnostics": { + "qwen/qwen3.5-plus-02-15": { + "child_refusal_rate": 0.0546875, + "child_zero_selection_or_refusal_rate": 0.0546875, + "child_zero_selection_substantive_rate": 0.0 + }, + "qwen/qwen3.5-plus-20260420": { + "child_refusal_rate": 0.0, + "child_zero_selection_or_refusal_rate": 0.0, + "child_zero_selection_substantive_rate": 0.0 + }, + "qwen/qwen3.6-plus": { + "child_refusal_rate": 0.0, + "child_zero_selection_or_refusal_rate": 0.0, + "child_zero_selection_substantive_rate": 0.0 + }, + "qwen/qwen3.7-plus": { + "child_refusal_rate": 0.0, + "child_zero_selection_or_refusal_rate": 0.0, + "child_zero_selection_substantive_rate": 0.0 + } + }, + "collapse_handling": "zero-substantive items make the containing axis coordinate unavailable for that model; bootstrap draws with a zero-coverage model/axis are invalid; family/trend/LOO metrics require all four finite coordinates and are otherwise an explicit unavailable result", + "constant_family_rmse": 0.07920916692361614, + "constant_family_rmse_ci95": [ + 0.07029038942655565, + 0.090037860156031 + ], + "constant_family_rmse_se": 0.004982451191867189, + "constant_noise_floor_mean": 0.013200677009896994, + "coord_ci95": { + "qwen/qwen3.5-plus-02-15": [ + [ + 0.75390625, + 0.7495039682539683 + ], + [ + 0.790625, + 0.771462673611111 + ] + ], + "qwen/qwen3.5-plus-20260420": [ + [ + 0.55859375, + 0.7615265376984126 + ], + [ + 0.59921875, + 0.7945188492063492 + ] + ], + "qwen/qwen3.6-plus": [ + [ + 0.70234375, + 0.7971137152777777 + ], + [ + 0.7609375, + 0.822420634920635 + ] + ], + "qwen/qwen3.7-plus": [ + [ + 0.6866992187500001, + 0.8193204365079365 + ], + [ + 0.76484375, + 0.8485863095238094 + ] + ] + }, + "coord_se": { + "qwen/qwen3.5-plus-02-15": [ + 0.00936839754486294, + 0.005779626357293611 + ], + "qwen/qwen3.5-plus-20260420": [ + 0.01045546953807998, + 0.008414758589596337 + ], + "qwen/qwen3.6-plus": [ + 0.015462501184190536, + 0.006650011173460525 + ], + "qwen/qwen3.7-plus": [ + 0.020434011492695057, + 0.007459677208890916 + ] + }, + "coverage": { + "qwen/qwen3.5-plus-02-15": { + "Abortion": 1.0, + "Attending peaceful demonstrations": 1.0, + "ChildQualities": 0.9453125, + "God": 1.0, + "Homosexuality": 1.0, + "Joining in boycotts": 1.0, + "Religion": 1.0, + "Signing a petition": 1.0, + "dealing with people?": 0.9453125 + }, + "qwen/qwen3.5-plus-20260420": { + "Abortion": 1.0, + "Attending peaceful demonstrations": 1.0, + "ChildQualities": 1.0, + "God": 1.0, + "Homosexuality": 1.0, + "Joining in boycotts": 1.0, + "Religion": 1.0, + "Signing a petition": 1.0, + "dealing with people?": 1.0 + }, + "qwen/qwen3.6-plus": { + "Abortion": 1.0, + "Attending peaceful demonstrations": 1.0, + "ChildQualities": 1.0, + "God": 1.0, + "Homosexuality": 1.0, + "Joining in boycotts": 1.0, + "Religion": 1.0, + "Signing a petition": 1.0, + "dealing with people?": 1.0 + }, + "qwen/qwen3.7-plus": { + "Abortion": 1.0, + "Attending peaceful demonstrations": 1.0, + "ChildQualities": 1.0, + "God": 1.0, + "Homosexuality": 1.0, + "Joining in boycotts": 1.0, + "Religion": 1.0, + "Signing a petition": 1.0, + "dealing with people?": 1.0 + } + }, + "family_bootstrap": { + "bootstrap_B": 1000, + "complete_draw_fraction": 1.0, + "complete_draws": 1000, + "constant_family_rmse_draws_mean": 0.0803271141879629, + "constant_family_rmse_draws_se": 0.004982451191867189, + "linear_trend_rmse_draws_mean": 0.07022643468549188, + "linear_trend_rmse_draws_se": 0.00649812277993048, + "loo_constant_mean_ci95": [ + 0.084038460643986, + 0.10719011065472368 + ], + "loo_constant_mean_draws_mean": 0.09545751207517682, + "loo_constant_mean_draws_se": 0.00603369466486572, + "loo_linear_mean_ci95": [ + 0.10178578915597014, + 0.1599172603475517 + ], + "loo_linear_mean_draws_mean": 0.1324065819800495, + "loo_linear_mean_draws_se": 0.014656720453106738, + "min_complete_draws_required": 100, + "status": "ok", + "valid_draws_per_model": { + "qwen/qwen3.5-plus-02-15": 1000, + "qwen/qwen3.5-plus-20260420": 1000, + "qwen/qwen3.6-plus": 1000, + "qwen/qwen3.7-plus": 1000 + } + }, + "family_point": { + "constant_family_rmse": 0.07920916692361614, + "linear_trend_rmse": 0.06958954455626604, + "loo": { + "constant_loo_mean": 0.0941587701606303, + "constant_loo_per_release": [ + 0.10511312720597471, + 0.043087196748553526, + 0.16722337401479925, + 0.06121138267319377 + ], + "linear_loo_mean": 0.13180142344503615, + "linear_loo_per_release": [ + 0.11421955351144603, + 0.04002699055118485, + 0.16201890071921912, + 0.21094024899829453 + ] + }, + "status": "ok" + }, + "linear_noise_floor_mean": 0.010376662428162988, + "linear_trend_rmse": 0.06958954455626604, + "linear_trend_rmse_ci95": [ + 0.05728500776210495, + 0.08291809923509534 + ], + "linear_trend_rmse_se": 0.00649812277993048, + "loo": { + "constant_loo_mean": 0.0941587701606303, + "constant_loo_per_release": [ + 0.10511312720597471, + 0.043087196748553526, + 0.16722337401479925, + 0.06121138267319377 + ], + "linear_loo_mean": 0.13180142344503615, + "linear_loo_per_release": [ + 0.11421955351144603, + 0.04002699055118485, + 0.16201890071921912, + 0.21094024899829453 + ] + }, + "loo_constant_mean_ci95": [ + 0.084038460643986, + 0.10719011065472368 + ], + "loo_constant_mean_se": 0.00603369466486572, + "loo_linear_mean_ci95": [ + 0.10178578915597014, + 0.1599172603475517 + ], + "loo_linear_mean_se": 0.014656720453106738, + "p_constant_noise_ge_observed": 0.0, + "p_linear_noise_ge_observed": 0.0, + "point_coords_xy_per_model": { + "qwen/qwen3.5-plus-02-15": [ + 0.7734375, + 0.759920634920635 + ], + "qwen/qwen3.5-plus-20260420": [ + 0.57890625, + 0.7782738095238094 + ], + "qwen/qwen3.6-plus": [ + 0.73203125, + 0.8100198412698413 + ], + "qwen/qwen3.7-plus": [ + 0.728125, + 0.8340773809523808 + ] + }, + "point_status": "ok", + "refusal": { + "qwen/qwen3.5-plus-02-15": 0.012152777777777778, + "qwen/qwen3.5-plus-20260420": 0.0, + "qwen/qwen3.6-plus": 0.0, + "qwen/qwen3.7-plus": 0.0 + }, + "source_shapes": { + "qwen/qwen3.5-plus-02-15": { + "answer_list_question_indices": 40, + "numbered_prefix_labels": 2, + "positional_labels": 86 + }, + "qwen/qwen3.5-plus-20260420": { + "positional_labels": 127, + "q_positional_labels": 1 + }, + "qwen/qwen3.6-plus": { + "answer_list_question_indices": 16, + "positional_labels": 109, + "q_positional_labels": 3 + }, + "qwen/qwen3.7-plus": { + "canonical_schema": 128 + } + }, + "unavailable_items": { + "qwen/qwen3.5-plus-02-15": { + "Survival <-> Self-expression": [], + "Traditional <-> Secular-Rational": [] + }, + "qwen/qwen3.5-plus-20260420": { + "Survival <-> Self-expression": [], + "Traditional <-> Secular-Rational": [] + }, + "qwen/qwen3.6-plus": { + "Survival <-> Self-expression": [], + "Traditional <-> Secular-Rational": [] + }, + "qwen/qwen3.7-plus": { + "Survival <-> Self-expression": [], + "Traditional <-> Secular-Rational": [] + } + } + }, + "release_years": [ + 2026.1269601725012, + 2026.2507596714865, + 2026.3182321156773, + 2026.4206679033487 + ], + "shift_pairing": "independent draws (protocols not pairable)" +} diff --git a/slop/research/wvs/20260919_respondent_packet/budget.json b/slop/research/wvs/20260919_respondent_packet/budget.json index 8faa319..c922e0e 100644 --- a/slop/research/wvs/20260919_respondent_packet/budget.json +++ b/slop/research/wvs/20260919_respondent_packet/budget.json @@ -1,14 +1,15 @@ { - "completed_phases": 3, + "completed_phases": 516, "completed_phases_without_provider_cost": 0, - "conservative_spent_usd": "0.02135488", + "conservative_spent_usd": "0.447093766", "eval_versions": [ "wvs-respondent-packet-v1", "wvs-respondent-packet-v2" ], - "failed_phases_charged_at_bound": 6, + "failed_phases_charged_at_bound": 8, + "finished_utc": "2026-09-19T11:13:41.750461+00:00", "hard_cap_usd": "5", - "provider_reported_spent_usd": "0.00212416", - "reserved_usd": "0E-8", + "provider_reported_spent_usd": "0.419875846", + "reserved_usd": "0E-9", "schema": 2 } diff --git a/slop/research/wvs/20260919_respondent_packet/pueue_task_1788_clean.log b/slop/research/wvs/20260919_respondent_packet/pueue_task_1788_clean.log new file mode 100644 index 0000000..dedfaa5 --- /dev/null +++ b/slop/research/wvs/20260919_respondent_packet/pueue_task_1788_clean.log @@ -0,0 +1 @@ +panel complete diff --git a/slop/research/wvs/20260919_respondent_packet/pueue_task_1788_status.json b/slop/research/wvs/20260919_respondent_packet/pueue_task_1788_status.json new file mode 100644 index 0000000..c98c0a7 --- /dev/null +++ b/slop/research/wvs/20260919_respondent_packet/pueue_task_1788_status.json @@ -0,0 +1,18 @@ +{ + "id": 1788, + "command": "scripts/wvs_api/10_respondent_packet_v2_panel.sh", + "path": "/workspace/2026/lite/moralmaps", + "group": "api", + "label": "why: compare human-format respondent packets with dense WVS on four Qwen Plus releases; resolve: audit uncertainty, refusals, family scatter and release trend without publishing", + "status": { + "Done": { + "enqueued_at": "2026-09-19T18:22:06.767920870+08:00", + "start": "2026-09-19T18:22:06.906420644+08:00", + "end": "2026-09-19T19:13:42.808979385+08:00", + "result": "Success" + } + }, + "clean_log": "pueue_task_1788_clean.log", + "clean_log_lines": 1, + "raw_log_bytes": 15 +} diff --git a/slop/research/wvs/20260919_respondent_packet/records/qwen__qwen3.5-plus-02-15/packets.jsonl b/slop/research/wvs/20260919_respondent_packet/records/qwen__qwen3.5-plus-02-15/packets.jsonl index 7e3b8c6..58ea073 100644 --- a/slop/research/wvs/20260919_respondent_packet/records/qwen__qwen3.5-plus-02-15/packets.jsonl +++ b/slop/research/wvs/20260919_respondent_packet/records/qwen__qwen3.5-plus-02-15/packets.jsonl @@ -2,3 +2,517 @@ {"eval_version": "wvs-respondent-packet-v2", "event": "request_started", "model": "qwen/qwen3.5-plus-02-15", "packet": 0, "payload": {"max_tokens": 2048, "messages": [{"content": "You are one person answering a social values survey. 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Never justifiable\n B. 2\n C. 3\n D. 4\n E. 5\n F. 6\n G. 7\n H. 8\n I. 9\n J. Always justifiable\nChoose exactly one option; if none fits exactly, choose the closest. Then give a short English reason in at most eight words.\n\n4. Please tell me for each of the following statements whether you think it can always be justified, never be justified, or something in between, using this card.\n\nHomosexuality\n A. Never justifiable\n B. 2\n C. 3\n D. 4\n E. 5\n F. 6\n G. 7\n H. 8\n I. 9\n J. Always justifiable\nChoose exactly one option; if none fits exactly, choose the closest. Then give a short English reason in at most eight words.\n\n5. Generally speaking, would you say that most people can be trusted or that you need to be very careful in dealing with people?\n A. Most people can be trusted\n B. Need to be very careful\nChoose exactly one option; if none fits exactly, choose the closest. Then give a short English reason in at most eight words.\n\n6. 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Please retry shortly, or add your own key to accumulate your rate limits: https://openrouter.ai/settings/integrations\",\"provider_name\":\"Alibaba\",\"is_byok\":false,\"limit_source\":\"upstream_provider_shared_pool\",\"remedy_hint\":\"Retry shortly, add your own provider key (https://openrouter.ai/settings/integrations), or route to another provider with provider routing: https://openrouter.ai/docs/features/provider-routing\"}},\"user_id\":\"user_2ffkoR4mYsVn0rZWphIZivDqvFW\",\"openrouter_metadata\":{\"requested\":\"qwen/qwen3.5-plus-20260420\",\"strategy\":\"direct\",\"region\":\"PER\",\"summary\":\"available=1\",\"attempt\":1,\"is_byok\":false,\"endpoints\":{\"total\":1,\"available\":[{\"provider\":\"Alibaba\",\"model\":\"qwen/qwen3.5-plus-20260420\",\"selected\":false}]},\"generation_time\":631}}", "status_code": 429} +{"attempt": 2, "error": "Client error '429 Too Many Requests' for url 'https://openrouter.ai/api/v1/chat/completions'\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/429", "error_type": "HTTPStatusError", "eval_version": "wvs-respondent-packet-v2", "event": "request_attempt_failed", "model": "qwen/qwen3.5-plus-20260420", "payload_sha256": "c39836bbfdcc4e01871495765f2f70b1ebc36e067a5070a092481262e367936d", "recorded_at_utc": "2026-09-19T10:52:58.811013+00:00", "reserved_bound_usd": "0.0039936", "response_text": "{\"error\":{\"message\":\"Provider returned error\",\"code\":429,\"metadata\":{\"raw\":\"qwen/qwen3.5-plus-20260420 is temporarily rate-limited upstream. Please retry shortly, or add your own key to accumulate your rate limits: https://openrouter.ai/settings/integrations\",\"provider_name\":\"Alibaba\",\"is_byok\":false,\"limit_source\":\"upstream_provider_shared_pool\",\"remedy_hint\":\"Retry shortly, add your own provider key (https://openrouter.ai/settings/integrations), or route to another provider with provider routing: https://openrouter.ai/docs/features/provider-routing\"}},\"user_id\":\"user_2ffkoR4mYsVn0rZWphIZivDqvFW\",\"openrouter_metadata\":{\"requested\":\"qwen/qwen3.5-plus-20260420\",\"strategy\":\"direct\",\"region\":\"PER\",\"summary\":\"available=1\",\"attempt\":1,\"is_byok\":false,\"endpoints\":{\"total\":1,\"available\":[{\"provider\":\"Alibaba\",\"model\":\"qwen/qwen3.5-plus-20260420\",\"selected\":false}]},\"generation_time\":970}}", "status_code": 429} +{"attempt": 3, "eval_version": "wvs-respondent-packet-v2", "event": "request_attempt_completed", "model": "qwen/qwen3.5-plus-20260420", "payload_sha256": 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