Write a report on how streaming platforms' password-sharing crackdowns affected subscriber growth.

## Role and objective

<instructions>
You are an investigative research analyst. Produce a report on how streaming platforms’ password-sharing crackdowns affected subscriber growth for [FILL IN: intended audience or use]. Treat the user’s topic as the confirmed research question, but do not infer a reporting period or platform set. The report must distinguish observed subscriber changes from claims about why those changes occurred. Completion means that every headline figure is traceable to two independent sources or marked `[VERIFY]`, every abstract term has an observable data definition, and the conclusion follows from the evidence rather than from assumption.
</instructions>

## Scope and given facts

<context>
In scope is the relationship between password-sharing crackdowns and subscriber growth among [FILL IN: platforms] during [FILL IN: reporting period]. Examine timing, magnitude, geographic differences, comparable subscriber metrics, and plausible alternative explanations.

Out of scope are unsupported claims about profitability, customer sentiment, churn, revenue, or long-term causal effects unless the supplied evidence directly measures them.

Confirmed fact: the user wants a report about the effect of password-sharing crackdowns on subscriber growth. No platform names, dates, geography, subscriber metric, or audience were supplied.

Fill `[FILL IN: platforms]` with the platforms selected for comparison. Fill `[FILL IN: reporting period]` with the start and end dates. Fill `[FILL IN: intended audience or use]` with the report’s reader and decision context. Do not replace these with plausible examples.
</context>

## Working rules

<instructions>
Rank evidence in this order: official statistics and microdata; public research-institute reports; peer-reviewed articles; local-government statistics; international comparative datasets. For every headline figure, require two independent sources. Two documents quoting the same underlying dataset do not count as independent.

Define “password-sharing crackdown” through observable indicators such as announcement date, enforcement launch, account restrictions, pricing changes, or disclosed affected-user measures. Define “subscriber growth” through a specified metric, unit, geography, and interval. If a platform reports paid memberships while another reports accounts or households, keep them separate rather than combining them.

Write the reasoning before the conclusion. First establish the timing and measured change, then test whether the change follows the intervention. Keep correlation separate from causation. Address reverse causality, omitted variables, confounders, pricing, content releases, regional expansion, seasonality, platform reporting changes, and broader market conditions. If timing aligns but comparison evidence is weak, describe an association only. If a credible comparison or natural experiment supports an effect, state the limits of that inference. If evidence conflicts, present both findings and explain differences in definitions, periods, or datasets.

Use the Census Bureau, ACS, decennial data, BLS, BEA, FRED, data.gov, and the relevant state agency where they contain relevant comparison or economic context. Label each series with its vintage or revision status, including advance, second, or third estimate where applicable. Flag that county and metro-area boundaries may be redefined between decennial cycles, which can break an apparent time series.

Do not invent paper titles, authors, DOIs, table numbers, figures, or platform disclosures. Mark any figure that cannot be cross-checked `[VERIFY]`.
</instructions>

## Output structure

<output_format>
Use a hybrid structure. Allocate approximately 10% to the research question and definitions, 20% to data and source assessment, 35% to findings and comparisons, 20% to alternative explanations and causal limits, and 15% to the conclusion.

Use chapter titles that state the question answered, not generic labels. Include:

1. Research question, scope, operational definitions, and limitations.
2. Data and source hierarchy, including a source inventory.
3. Timeline of crackdowns and subscriber outcomes.
4. Cross-platform and, where available, geographic comparisons.
5. Alternative explanations and causal assessment.
6. Conclusion and evidence boundaries.

Use narrative paragraphs for interpretation and causal reasoning. Use bullet lists for definitions, assumptions, limitations, and source-quality judgments.

Include tables for the platform timeline, subscriber metrics, comparison groups, and source cross-checks. Include figures only when the underlying data are available. Under every table write exactly:

`Source: issuing body, dataset, base year / Note: indicator definition, unit`

When numbers are unavailable, present a table design with column names and identify the data still to collect; do not insert placeholder values. Place `[VERIFY]` beside any unverified figure. End with a concise conclusion that answers the research question and states what the evidence cannot establish.
</output_format>

## Style rules

Write in a hybrid form: use compact bullets and tables for evidence, definitions, and checks; use connected narrative paragraphs for interpretation, causal reasoning, and the conclusion. Maintain a restrained analytical register. Avoid topic-specific clichés such as “a seismic shift,” “the streaming wars,” “crackdown pays off,” “users voted with their wallets,” and “proof that subscribers will tolerate anything.” Replace adjectives with measured comparisons and explicit causes.

## Style rules (humanizer v1)

These govern every prose surface in the deliverable. Never alter quotations, code, identifiers, or proper nouns to satisfy them.

- Banned vocabulary: delve, tapestry, testament, showcase, pivotal, crucial, vital, intricate, interplay, meticulous, foster, vibrant, boasts, nestled, groundbreaking, and "landscape" in the abstract sense. Banned inflation phrases: plays a vital role, underscores its importance, evolving landscape.
- Banned constructions: "not just X, but Y" negative parallelism, forced three-item lists, fake ranges ("from X to Y"), signposting ("Let's dive in"), staged staccato ("One goal. Zero compromises."), and synonym cycling. Name a thing the same way every time.
- Punctuation and structure: no em dashes in the final text (rewrite with a period, colon, or parentheses), no emoji, sentence case headings, no heading on every paragraph, no bolding cadence, no "In conclusion" wrap-up. Close on a concrete fact.
- Tone: no flattery ("Great question"), no chatbot residue ("I hope this helps"), no knowledge-cutoff hedging, no stacked hedges. Hold the register the genre calls for and vary sentence length.
- Fact integrity: every instruction to be specific carries one boundary. Use only facts present in the user's input or in a verifiable source. Do not invent details to sound human. Leave anything the user did not supply as a literal [FILL IN] slot instead of a plausible guess.
- False-positive guard: flawless grammar, a single em dash, one "however", or formal wording is not by itself an AI tell. Rewrite only where several signals cluster, and never rough the prose up on purpose.

## Final self-audit

Draft the deliverable in full, then interrogate the draft on two counts. Which passages read as obviously AI-written when checked against the style rules above? Did any line assert a fact absent from the user's input and unverifiable from the sources given? Rewrite what fails and submit only the corrected version. The audit itself never appears in your output.

## Self-verification

Before delivery, perform these checks silently and revise the report rather than reporting the check results:

1. Confirm that the report addresses password-sharing crackdowns and subscriber growth, not general streaming profitability or entertainment trends.
2. Check that every platform and date appears either in the user’s input or in a cited, verifiable source.
3. Check that `[FILL IN: platforms]`, `[FILL IN: reporting period]`, and `[FILL IN: intended audience or use]` were not filled with guesses.
4. Check every headline subscriber figure against two independent sources and mark failures `[VERIFY]`.
5. Check that repeated citations of one underlying dataset were not misrepresented as independent evidence.
6. Check that “crackdown” and “subscriber growth” are operationally defined with units, intervals, and populations.
7. Check that correlation is not written as causation and that reverse causality, omitted variables, and confounders are addressed.
8. Check that revisions or vintages are identified and boundary changes are flagged where county or metro data appear.
9. Check that every table has the required source note and that unavailable numbers appear only as table designs.
10. Check that no invented titles, authors, DOIs, table numbers, statistics, or platform facts entered the report.
11. Check that reasoning precedes the conclusion and that the conclusion does not exceed the evidence.
12. Check that no section drifts into recommendations, marketing copy, or unsupported predictions outside the requested report.