Write a report surveying how small companies are preparing for ESG disclosure

## Role and objective

You are a research analyst producing an evidence-based report on how small companies are preparing for ESG disclosure. Write for [FILL IN: intended readership], using only verifiable information from the defined jurisdiction and study period. Treat “small companies” and “ESG disclosure” as operational concepts, not assumed categories.

Produce a research report with documented sources, analytical comparisons, tables, figures or proposed table designs, and clearly bounded conclusions. The report is complete only when every headline figure is supported by two independent sources, every abstract term is tied to observable indicators, and all unsupported figures are marked `[VERIFY]`.

## Scope and given facts

The confirmed subject is a survey of preparation for ESG disclosure among small companies. Cover preparation activities such as governance, data collection, materiality assessment, controls, reporting technology, assurance readiness, external advice, and decisions about whether or how to disclose, only where the evidence supports them.

The following remain unconfirmed and must not be guessed:

- **Geography:** `[FILL IN: geographic jurisdiction or countries to cover]` — insert the target geography and reporting context.
- **Study period:** `[FILL IN: reference date or study period]` — insert the period used to select and compare evidence.
- **Company definition:** `[FILL IN: definition of small companies]` — insert the employee, revenue, assets, or other inclusion rule.
- **Audience:** `[FILL IN: intended readership]` — insert the principal readers and their decision need.
- **Report length:** `[FILL IN: report length or page limit]` — insert the required limit, if any.

Exclude unsupported claims about all small companies, legal obligations that have not been verified, and general ESG trends that do not describe preparation for disclosure. Do not convert survey responses into proof of actual reporting capability without stating the limitation.

## Working rules

Select and state the operational definitions before synthesis:

1. Define “small company” using the supplied threshold; if none is supplied, preserve the slot and report how each source defines its population.
2. Break “ESG disclosure preparation” into observable indicators: assigned responsibility, policy adoption, materiality or topic assessment, baseline data collection, emissions or other metric measurement, controls, systems, supplier data processes, assurance planning, external support, and publication or non-publication decisions.
3. Distinguish preparation status from disclosure outcome. Classify evidence as planned, initiated, implemented, completed, or reported only when the source supports that classification.
4. Separate correlation from causation. Address reverse causality, omitted variables, and confounders such as company size within the small-company category, sector, regulatory exposure, customer pressure, financing needs, and prior reporting experience.

Rank sources in this order: official statistics and microdata; public research institute reports; peer-reviewed articles; local government statistics; international comparative datasets. Require two independent sources for every headline figure. Two documents citing the same underlying dataset are not independent. Record the issuing body, dataset, publication date, methodology, sample, geography, definition, and limitations.

For US evidence, search the Census Bureau, including ACS and decennial data where relevant, BLS, BEA, FRED, data.gov, and the relevant state agency. Use the applicable repositories for the selected geography rather than importing US sources without justification. Add the vintage or revision label to every series, including advance, second, or third estimates. Flag that county and metro-area boundaries may be redefined between decennial cycles, which can break a time series without warning.

If a figure cannot be cross-checked, mark it `[VERIFY]` and explain what remains to be checked. Never invent paper titles, authors, DOIs, table numbers, sample sizes, dates, or statistics.

## Output structure

Use the following chapter plan and allocate approximately 10% of the report to each of Chapters 1 and 2, 20% to Chapter 3, 25% to Chapter 4, 20% to Chapter 5, and 15% to Chapter 6, reserving the remainder for references and limitations:

1. **Executive summary** — state the main findings, evidence strength, and unresolved gaps without introducing unsupported figures.
2. **Definitions, population, and method** — define the geography, period, small-company threshold, ESG disclosure preparation indicators, search method, source hierarchy, and independence test.
3. **Current preparation practices** — compare governance, data, metrics, controls, systems, assurance, advisers, and disclosure decisions.
4. **Drivers, barriers, and variation** — examine regulatory, customer, investor, lender, sector, capability, and cost factors; distinguish observed association from causal interpretation.
5. **Comparative assessment** — compare preparation by company subgroup, sector, geography, or reporting maturity only where samples and definitions are comparable.
6. **Implications and evidence gaps** — identify practical implications, measurement weaknesses, unresolved questions, and what additional data would test the conclusions.

Include a methods table, an evidence matrix, a preparation-indicator table, and comparison tables where data permit. Include figures only when their values are verified. For any unavailable number, present a design proposal showing the intended rows, columns, unit, population, denominator, source, and data still to collect; do not insert placeholder values.

Under every table, write exactly: `Source: issuing body, dataset, base year / Note: indicator definition, unit`.

## Style rules

Use a hybrid style. Present definitions, evidence ratings, comparisons, source records, and methodological checks in itemized or tabular form. Present findings, interpretations, limitations, and transitions in concise narrative paragraphs. Use an analytical, non-promotional register. Avoid topic-specific clichés such as “ESG is no longer optional,” “a one-size-fits-all approach,” “the road ahead,” and “moving the needle.” Do not use rhetorical certainty where evidence is mixed.

## 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

1. Confirm that the deliverable is a report surveying preparation for ESG disclosure, not a generic ESG overview or an implementation plan.
2. Confirm that the geography, study period, company definition, and readership are either supplied or retained as explicit `[FILL IN: ...]` slots.
3. Check that every abstract term—“small company,” “ESG,” and “preparation”—has observable indicators or a stated source-specific definition.
4. Check every headline figure against two independent sources and verify that the sources do not merely cite the same underlying dataset.
5. Confirm that every US series names its repository and vintage or revision label, where US evidence is used.
6. Check county and metro-area comparisons for boundary changes between decennial cycles before treating them as continuous time series.
7. Identify any facts added beyond the supplied request and remove them unless they are supported by a cited, verifiable source.
8. Confirm that no `[FILL IN: definition of small companies]`, geography, period, audience, or other slot was filled arbitrarily.
9. Check that unsupported numbers, paper titles, authors, DOIs, table numbers, and causal claims are absent or visibly marked `[VERIFY]`.
10. Confirm that correlation is not presented as causation and that reverse causality, omitted variables, and confounders are addressed.
11. Confirm that each required chapter, table design, source note, comparison, and limitations section is present.
12. Remove material drifting outside how small companies prepare for ESG disclosure, then deliver the report in plain markdown.