US DOL List of Goods (Child/Forced Labor): Intelligence Source Guide

The US Labor Department names commodity-and-country pairs it has reason to believe are produced with child or forced labour. It is the standard starting point for supply-chain screening, and it names no company, facility or shipment.

At a glance

Source	US DOL List of Goods (Child/Forced Labor)
Category	Conflict, Crime & Human Security › Human Trafficking & Child Protection
Homepage	https://www.dol.gov/agencies/ilab/reports/child-labor/list-of-goods
Machine interface	`https://www.dol.gov/sites/dolgov/files/ILAB/child_labor_reports/tda2023/List-of-Goods.json`
Format	`JSON`
Access	Open — no account required
Disciplines	Supply Chain Intelligence, Human Intelligence
Mission domains	Forced Labour & Modern Slavery

Goods produced by forced/child labor by country. — as catalogued in the platform’s own source registry.

The List of Goods Produced by Child Labor or Forced Labor is compiled by the Bureau of International Labor Affairs at the US Department of Labor under a statutory mandate originating in the Trafficking Victims Protection Reauthorization Act. It has been published since 2009 and is updated on roughly a biennial cycle. Each entry is a pair — a good and the country it comes from — annotated with which of three findings applies: child labour, forced labour, or forced child labour. Entries are grouped by sector, principally agriculture, manufacturing, and mined or quarried goods. The evidentiary standard is 'reason to believe', assessed against international labour standards rather than against US law, and the evidence base is documentary: published research, ILAB-funded field studies, government and international organisation reporting, submissions from unions, NGOs and industry, and public comment. Recent editions cover well over a hundred distinct goods across dozens of countries, and the list grows at each revision as new research lands. The list is distributed as a report and as machine-readable data, and it sits alongside two related ILAB products that are frequently confused with it: an annual country-by-country assessment of government efforts against the worst forms of child labour, and a much shorter procurement list issued under executive order which does carry direct legal consequences for US federal contractors. ILAB also publishes tooling that maps listed goods to trade data, which is how the list acquires the tariff-code dimension it does not natively have.

This list does a job no enforcement instrument can do: it tells you where to look before anyone has been caught. Import bans, entity lists and customs detentions are consequences of established findings against specific parties, and by the time a company appears on one, the exposure has already crystallised. The List of Goods is upstream of all of that. It is a research product describing conditions at the commodity-and-origin level, which is exactly the resolution at which sourcing decisions are made and at which a due-diligence programme can act pre-emptively. For SUPPLYINT work it functions as the risk prior: any bill of materials whose inputs trace to a listed pair inherits a documented, government-attested reason for heightened scrutiny, and that attestation is what makes a procurement decision defensible to a regulator, an auditor or a court. Its second function is as a translation layer between human-rights research and commercial data. The underlying evidence lives in field studies and NGO reporting that a compliance system cannot consume; the list renders that evidence as a structured pair that joins to supplier records, customs declarations and tariff classifications. Its third function is diplomatic and reputational: the act of listing exerts pressure on producing governments and industries, and delisting is itself a signal about reform — which is why the listing and delisting decisions are contested, and why you should read the accompanying narrative rather than only the table.

Who publishes it, and why that matters

ILAB is a bureau of a cabinet department, so the list is a government product with a statutory mandate, funded through appropriations and subject to the politics of both. That has a specific consequence for reliability: the methodology is documented and consistently applied, and the research is genuinely independent in its execution, but the decision to list or delist a good from a partner country is made inside a department that also has trade relationships to manage, and the process has been criticised by both directions — as too slow to list politically sensitive origins, and as unfairly stigmatising producing economies. The right posture is to trust the evidence characterisation while treating the completeness of the list as a political as well as an empirical question. Funding and staffing for ILAB's research programme have fluctuated with administrations, which affects how much new field evidence is generated between editions, and the biennial cadence has occasionally slipped. The mandate itself is durable — it is written into law and has been reauthorised repeatedly — so the product's continuation is not in serious doubt, but the depth of each edition depends on money that is appropriated afresh. Check the publication date of the edition you are using and whether a newer one has landed; users citing a superseded edition is the most common avoidable error with this source.

Provenance is the first question to ask of any dataset and the one most often skipped. Who collects it, what their incentive is, whether they publish a methodology, and whether they correct the record when they get something wrong all bear directly on how much weight a finding drawn from it can carry.

What a record actually contains

The fields you will be working with, what each one means, and whether it is something you can pivot on. Read the meanings carefully — more analysis is wrecked by misreading a field than by failing to find one, and a field that looks like an observation is often an inference.

Field	Type	What it means	Pivot value
`good`	string	The commodity, named in ordinary English — cotton, cocoa, bricks, gold, garments, sugarcane, fish. It is not a tariff code, not a product specification and not a brand, and the naming granularity varies between entries.	Tariff classification via a mapping step you perform, commodity trade flows, supplier and input-material registers.
`country`	string	The country of production associated with the finding. This is where the labour occurred, which for processed commodities is often not the country of export shown on a customs declaration.	Country dashboards, trade-flow analysis, transshipment and origin-laundering assessment.
`child_labor`	enum	Whether the finding includes child labour as defined by international standards. Note that this covers work that is hazardous or age-inappropriate, not merely any work performed by a minor, and the distinction matters when characterising an entry publicly.	Sector risk scoring; alignment with ILO conventions in a supplier code of conduct.
`forced_labor`	enum	Whether the finding includes forced labour: work exacted under menace of penalty and not offered voluntarily. This is the flag that connects to import-enforcement regimes, which are generally built around forced labour rather than child labour.	Customs enforcement exposure, entity-list correlation, financial-crime typologies.
`forced_child_labor`	enum	A distinct finding where both conditions apply. Treat it as its own category rather than as the intersection of the other two, because ILAB assigns it deliberately and it carries the strongest evidentiary weight in the set.	Escalation prioritisation; the entries most likely to attract regulatory attention first.
`sector`	enum	The broad production sector — agriculture, manufacturing, mined or quarried goods, and a small number of other categories. Useful for portfolio-level screening and for choosing which audit methodology is even applicable.	Due-diligence programme design; matching an entry to the right verification technique.
`edition_year`	int	The publication cycle in which the entry appears. Entries persist across editions unless removed, so presence in the current edition is a live finding while absence from an older one is not evidence of anything.	Change analysis between editions; identification of newly listed and delisted pairs.
`new_entry_flag`	enum	Whether a pair was added in this edition. New additions are the highest-value part of any update because they represent evidence that has only just become actionable and that most competitors have not yet screened for.	Priority review queue; early-warning triggers for procurement categories.
`removal_status`	enum	Whether a previously listed pair has been removed. Removal signals that ILAB assessed the evidence as no longer supporting the finding, which is a claim about the evidence base and not necessarily a certification that conditions have improved.	Reform-trajectory analysis; sanity-checking a producer government's own claims.
`hs_code`	string	Not present in the list itself. Tariff classification is supplied by ILAB's separate trade tooling or by your own mapping, and the mapping is inferential and lossy because one listed good can span many codes and one code can cover listed and unlisted origins.	Customs declarations, import value analysis, supplier shipment records — but only after you have documented and owned the mapping.
`company`	string	Also not present, and this is the field users most often assume exists. The list makes no company-level or facility-level finding whatsoever. Company-level exposure comes from customs enforcement actions, entity lists and your own supply-chain tracing.	Nothing directly. Company identification requires an entirely separate evidentiary chain that you must build and be able to defend.
`source_evidence`	array	The underlying research cited in the report narrative for each finding. This is where the actual analytical content lives, and reading it is what distinguishes a defensible risk assessment from a table lookup.	Primary research sources, field-study authors, regional and sectoral specialists worth contacting.

Coverage — and what is not in it

The list covers goods produced in foreign countries; goods produced within the United States are outside its mandate, which is a structural gap you should state plainly whenever presenting the list as a global risk map. Within that scope, coverage is broad but uneven, and its unevenness is systematic rather than random: a pair appears when credible documentary evidence exists, and credible documentary evidence requires researchers, unions, journalists or international organisations to have had enough access to produce it. Countries that permit independent labour research are therefore better represented than countries that do not, and some of the most closed economies carry short lists that reflect access rather than conditions. Sectoral coverage is deepest in agriculture and extractives, where field research is comparatively feasible, and thinner in dispersed home-based and informal production, which is where a great deal of child labour actually occurs. The temporal picture is coarse by design: the biennial cycle means an entry can lag the evidence by a year or more and the evidence can lag the conditions by longer still, so the list describes a persistent state rather than a current one. Entries accumulate across editions, giving a usable long baseline back to 2009, and the accompanying narratives provide the qualitative depth that the table alone lacks.

Known blind spots

Absence of evidence here is not evidence of absence. These are the conditions under which US DOL List of Goods (Child/Forced Labor) will not show you something that is nevertheless real:

No company, facility, farm or exporter is ever named, so the list cannot tell you that a specific supplier is implicated and cannot be used as the basis for an adverse finding against one.
United States production is out of scope entirely, which means a list presented as a global picture of forced and child labour silently excludes one of the world's largest agricultural and manufacturing economies.
Listing requires evidence, and evidence requires access. Countries that suppress independent research, bar journalists or prevent union organising are under-listed relative to reality, and their short entries should be read as a measure of opacity rather than of compliance.
The list names goods near the start of the chain. A finished product containing a listed input is not itself listed, so screening on the list alone misses everything that has been processed, blended or assembled downstream.
The biennial cadence introduces a structural lag of up to two years, on top of whatever lag existed between conditions on the ground and the research that documented them.
There are no volumes, values or shares. An entry does not tell you whether the practice affects a fraction of a percent of a country's output or most of it, and users routinely infer the latter from the mere fact of listing.
The good names are not tariff codes and the mapping between them is many-to-many, so any join to customs data is an inference you own and must be able to defend rather than a lookup.
Delisting is a statement about the evidence base, not a certification of remediation, and treating a removal as proof that a problem was solved is a mistake the accompanying narrative usually warns against.
Informal, home-based and family-enterprise production — a large share of global child labour — is systematically harder to document and therefore systematically under-represented across every edition.

Write the blind spot into the product. A statement that something “was not observed in US DOL List of Goods (Child/Forced Labor)” is defensible; a statement that it “did not happen” is not, and the difference is what survives cross-examination.

Access, licensing and what you may do with it

Access model: Open — no account required

Everything is public and free. The report itself is published on the ILAB website in narrative form with the full table of entries, and machine-readable data files are published alongside it, which is what makes this one of the few sources in the human-security category that can be ingested as data rather than parsed out of prose. There is no registration, no key and no licence acceptance step. In practice the friction is version management rather than access: editions are published to dated locations, older editions remain available, and it is easy to build against a path that a subsequent publication cycle supersedes. Pin the edition you ingested, record its publication date, and re-check for a new edition on a calendar reminder rather than relying on a URL to change under you. ILAB also publishes complementary tooling — a mobile presentation of the underlying data, guidance for building a compliance programme, and a trade tool that joins listed goods to US import data — and those are separate products with their own update cycles that you should register separately rather than assuming they move together.

Licence

As a work of the US federal government, the report and its data are generally in the public domain within the United States and are freely usable, redistributable and modifiable without permission. That is unusually permissive for a source of this significance, and it is why the list has propagated into commercial risk products, ESG ratings and procurement systems worldwide. Two cautions follow from that permissiveness rather than from any restriction. First, attribute anyway: the list carries authority because of who compiled it and under what mandate, and a derived dataset that drops the attribution loses the very property that made it worth using. Second, the public-domain status attaches to the government's text, not to third-party material quoted or reproduced within it, and some accompanying imagery and cited research is separately owned. If you are redistributing a transformed version, make the edition and the transformation explicit so downstream users can tell your inference from ILAB's finding.

Rate limits and fair use

This is a document and data-file source updated on a two-year cycle. There is no rate limit to respect and no reason to poll frequently. Fetch the current edition once, cache it permanently, and check for a new one quarterly at most — a monthly check is generous and a daily one is simply noise in your collection logs. Where you use the accompanying trade tooling, treat it as an interactive service rather than a bulk source and do not attempt to enumerate it. If you need the underlying trade data at scale, go to the customs statistics authority that publishes it rather than scraping a presentation layer built on top of it.

Licensing changes, and it changes without warning. A dataset that was free for research this year may not be free for commercial or evidential use next year. Confirm the current terms before you build a dependency on it, and record the terms you relied on alongside the data — the licence in force at the time of collection is part of the provenance.

Collecting it

How US DOL List of Goods (Child/Forced Labor) is actually pulled, in the order you would set it up. Prefer the bulk or export interface over per-item lookups wherever one exists: it is kinder to the publisher, faster for you, and gives a reproducible snapshot rather than a series of point-in-time answers you cannot reconstruct later.

Method	Format	Cadence	Notes
Structured data file	JSON	per edition, roughly biennial	The machine-readable representation of the entries. The cleanest ingest route; pin the edition path and record it, because a new cycle publishes to a new location.
Report narrative	HTML	per edition	Where the evidence, the methodology and the country context live. The table alone is not a risk assessment; the narrative is what makes an entry defensible.
Companion country assessments	HTML	annual	ILAB's separate annual review of government efforts, which supplies the governance dimension and updates more often than the list itself.
Procurement list under executive order	HTML	irregular	A much shorter, legally operative list for US federal contracting. Ingest it separately and never conflate it with the main list, because only one of them has direct contractual consequences.
Trade mapping tooling	HTML	periodic	ILAB's own join between listed goods and US import data. Useful as a reference mapping, but record it as ILAB's inference rather than adopting it silently as fact.
Prior editions	bulk	one-off	Retrieve every past edition once. The difference between editions — additions, removals, changed findings — is the most analytically valuable view of this source and it does not exist in any single file.

Ingesting it into the platform

Every step below is idempotent and cursor-based: interrupt one and it resumes from where it stopped rather than duplicating rows or losing progress. Collection is recorded per source, so a feed that quietly stops publishing shows up as a stale timestamp instead of silently thinning your coverage.

Register the edition, not the URL — Add the source in `sources.php` keyed by edition year with the publication date recorded, so `collect.php` tracks a versioned artefact rather than watching a path that will move at the next cycle.
Load entries as pairs with findings — Use `import.php` to create one record per good-country pair carrying the three finding flags, the sector and the edition. Resist the urge to collapse the flags into a single severity score at ingest; downstream consumers need them separately.
Normalise countries and goods separately — Map country names to ISO codes for `country.php`, and build a controlled vocabulary for goods with the raw ILAB string preserved. Good names vary between editions and an unmanaged vocabulary will silently split a commodity into two.
Build and label the tariff mapping — Attach tariff classifications as a separate, explicitly labelled inference layer with a confidence value and a stated basis. Never store an HS code as though ILAB supplied it; every downstream dispute about this source turns on that distinction.
Diff against the prior edition — Compute additions, removals and changed findings automatically and surface them as events. New entries are the highest-value output of an update cycle and they are invisible if you only ever hold the current snapshot.
Join to supplier and trade records — Correlate pairs against your own supplier register, country-of-origin declarations and commodity flows in `correlate.php` and `matrix.php`, producing a scored exposure view rather than a binary flag.
Separate this from enforcement data — Keep import-enforcement actions and entity listings in distinct record types on `sanctions.php`, because one carries legal consequence and the other carries risk signal, and merging them produces both false alarms and false comfort.
Expose to the mission areas — Surface exposure views on `human-trafficking.php` and `financial-crime.php`, and make the underlying evidence narrative reachable from every entry so that an analyst acting on a flag can see what it actually rests on.

Registered sources and their last-collected state are listed in sources.php, and the scheduled chain that keeps them current is in automation.php.

How it is wrong, and how to tell

Every dataset is wrong in characteristic ways. Knowing which ways is the difference between using a source and being used by one, and it is the part of source evaluation most often skipped because it is the part that takes work.

For what it claims to be, this is a strong and carefully constructed product. The methodology is published, the evidentiary standard is stated rather than implied, findings are traceable to cited research, and the annotation of which of the three findings applies is applied with discipline. Entries are not asserted casually; the process requires documentary evidence assessed against international standards, and ILAB is explicit that 'reason to believe' is a research threshold and not a legal determination. The quality risk is not in the entries that are present but in the shape of the whole: the list is a function of where research has been possible, and that shape correlates with press freedom, union access and government cooperation in ways that systematically favour listing open societies. There is also a political layer around listing and delisting decisions that is real, acknowledged by outside observers, and impossible to quantify from the data. Judge the individual entry as reliable and well-sourced. Judge the absence of an entry as uninformative. That asymmetry is the whole of the quality assessment.

Characteristic false positives

Reading a listed pair as a finding against a specific supplier, shipment or company. The list makes no company-level claim at all, and adverse action taken on that basis is both analytically unsupported and legally exposed.
Treating absence from the list as evidence of clean production. Absence usually reflects an absence of accessible research, and the most closed producing environments are the ones least likely to appear.
Assuming a listed good implicates all of that country's output of it. There are no volumes or shares in the data, and the practice may be confined to one region, one production model or one segment of the market.
Using ILAB's tariff mapping as though it were part of the finding. The mapping is inferential, many-to-many, and produced for a different purpose; adopting it silently converts a defensible risk signal into an indefensible customs claim.
Confusing this list with the shorter procurement list issued under executive order, or with customs enforcement instruments. Only some of those carry legal consequence, and the difference determines what action a finding can lawfully support.
Citing a superseded edition. Entries are added and removed at each cycle, and a claim built on a two-cycle-old table can be flatly wrong about the current position of a country or good.
Interpreting a removal as proof of remediation. Removal reflects ILAB's assessment of the current evidence base, which can change because conditions improved or because research capacity collapsed.
Screening only for listed goods and stopping there. Because the list names upstream commodities, a screen that does not trace inputs through processing and assembly will clear most of the products where the exposure actually sits.

None of these make the source unusable. They make it a source that requires corroboration before an assertion built on it goes into a product, which is true of every source and admitted by few.

Ageing

Two clocks run at different speeds. The individual entry ages slowly: the conditions the list describes are structural, and a finding about cocoa, bricks or cotton in a given country is rarely overtaken within a single cycle. The list as a whole ages on a hard two-year boundary, and the moment a new edition publishes, every prior edition becomes a historical document that should be retained but never quoted as current. The tariff mapping and any trade-value analysis built on it age fastest of all, because trade patterns, sourcing routes and transshipment behaviour shift continuously and a mapping built against one year's flows misdescribes the next. A stale record from this source is recognisable: it is a citation without an edition year, or a risk score in a procurement system that nobody has re-run since the list it was built from was superseded. Build the re-screen into a calendar obligation rather than into an intention, because the failure mode is silent — nothing breaks, the scores simply become wrong.

What this source feeds

A source is only worth what it lets you conclude. These are the disciplines that collect through it, the mission domains it serves and the data points it yields — every one is a tag, so you can follow any thread from here into the rest of the library.

Collected by these intelligence disciplines

Serves these mission domains

Forced Labour & Modern Slavery

Yields these data points

How each sector uses US DOL List of Goods (Child/Forced Labor)

The same dataset is worked very differently depending on who you are, what authority you hold, and what you are ultimately producing. A military analyst is supporting a commander’s decision; a journalist is meeting a publication standard; an NGO caseworker is protecting a person. The records are shared — the constraints, thresholds and outputs are not.

🎖 Military and defence

The direct application is defence procurement and contractor oversight. Defence supply chains reach deep into extractives, textiles and electronics inputs that appear on this list, and the compliance obligations attaching to federal contracting — particularly through the separate executive-order procurement list — are contractual and enforceable rather than advisory. Use the list to prioritise which input categories in a programme's bill of materials warrant origin tracing. There is a secondary use in operational assessment: pervasive forced labour in an extractive sector is a reliable indicator of armed-group or elite capture of that sector, which bears on conflict economy analysis in the same theatre.

🕵 National intelligence

Read it as an economic-coercion and governance dataset rather than as a human-rights one. State-organised forced labour is a policy instrument in some jurisdictions, and its presence in a strategic commodity — minerals, textiles, agricultural exports — connects directly to sanctions exposure, trade-enforcement action and the political economy of the producing state. The list is also a decent proxy for research access: comparing a country's list length with independent assessments of press freedom and union activity gives you a usable opacity signal. For FININT work, the listed pairs identify the trade lanes where forced-labour-linked value is most likely to be present in trade finance.

👮 Law enforcement

The list is intelligence, not evidence. It will not support a charge, a seizure or a search, and it names nobody. What it does is prioritise: it tells you which commodity flows into your jurisdiction carry documented production risk, which lets you focus labour-inspection, customs and financial-investigation resources where the base rate is highest. In jurisdictions with import-prohibition regimes, the list is the natural front end to the enforcement instrument, but the instrument requires its own evidence about specific goods and specific parties.

🔍 Private investigation and corporate security

This is the standard opening move in supply-chain due diligence and the standard place where a weak engagement stops. Screening a client's supplier register against listed pairs takes an afternoon; the actual work is tracing inputs upward through processing tiers to determine whether a listed commodity is in the product at all, and then building an evidentiary picture at facility level from customs records, corporate filings, satellite imagery, labour inspection reports and local press. Deliver the list result as a scoping output and be explicit with the client that it is not a finding about any of their suppliers.

📰 Journalism and OSINT media

It is a good story spine and a bad headline. The list supports reporting on the structural presence of forced and child labour in named commodity chains, with a government attestation behind it. It does not support naming a company, and a story that leaps from 'this commodity from this country is listed' to 'this brand uses forced labour' has skipped the entire evidentiary chain that would make it defensible. The strongest journalism using this source has treated the entry as a starting point and done the tracing work itself, usually with customs data and field reporting.

🌍 NGO, humanitarian and human rights

For advocacy and campaigning organisations, the list is leverage: it is a government finding, freely usable, that a company cannot dismiss as activist assertion. Use it to frame engagement with brands, to support submissions to regulators, and to argue for legislative extension in jurisdictions building their own due-diligence regimes. Field organisations also have a direct route into the source, because ILAB accepts public submissions of evidence, and a well-documented submission is one of the few ways a small organisation can move a national-level instrument.

🎓 University and research

The list is a well-documented, freely available panel dataset with more than a decade of editions, which makes it attractive for research on trade, labour standards and regulatory diffusion. The methodological hazard is that inclusion is endogenous to research access and to diplomatic relationships, so treating listing as an unbiased measure of underlying labour conditions will produce results that mostly reflect openness. Modelling the listing process itself — what predicts an addition or a removal — is the more defensible design and has produced better literature than treating the list as ground truth.

Playbook: working US DOL List of Goods (Child/Forced Labor) end to end

A repeatable sequence from first pull to finished product. Each phase states what you are trying to establish, not merely what to click — the objective is a defensible chain of reasoning, not a completed checklist.

Phase 1 — Pin the edition before anything else

Establish which edition you are working from, when it was published, and whether a newer one exists. Every downstream conclusion is edition-specific, and the commonest failure with this source is a risk assessment built on a superseded table that nobody re-ran.

Phase 2 — Read the methodology, then the narrative, then the table

In that order. The methodology tells you what 'reason to believe' means and what it does not; the narrative carries the evidence and the country context; the table is a summary of both. Analysts who start at the table produce screens that cannot survive a challenge from a supplier's counsel.

Phase 3 — Separate the three findings and keep them separate

Child labour, forced labour and forced child labour have different legal consequences, different remediation pathways and different enforcement regimes attached to them. Import-prohibition instruments generally key on forced labour. Collapsing the flags into one risk score destroys exactly the distinction that determines what action is available.

Phase 4 — Build the input trace, not just the product screen

Take each product in scope and decompose it into inputs, then trace each input upward through processing tiers to a country of production. The list operates at the commodity level, so a screen applied to finished goods will return almost nothing while the exposure sits two tiers up. This is the labour-intensive step and it is the one that produces actual findings.

Phase 5 — Own the tariff mapping explicitly

Where you join to customs or trade data, document the good-to-code mapping, record its basis, and store a confidence value with it. Expect one listed good to span several codes and several codes to include unlisted origins. When challenged, you must be able to show which part of your claim is ILAB's and which part is yours.

Phase 6 — Diff the editions to find what is new

Compare the current edition with the prior one and treat additions as a priority queue. New entries represent evidence that has just become citable, and acting on them before they propagate into commercial risk products is one of the few genuine timing advantages available in this domain.

Phase 7 — Layer enforcement data on top

Bring in customs detention actions, entity listings and import-prohibition findings as a separate layer in `sanctions.php`. Where an enforcement action and a listed pair coincide for the same commodity and origin, the risk is no longer prospective and the required response changes from monitoring to action.

Phase 8 — Check the opposite direction for absence bias

For each major sourcing country in scope, ask whether independent labour research is possible there. Where it is not, record an explicit 'unassessable' status rather than a low risk score. A supplier register in which the most opaque jurisdictions score best is a register that has quietly inverted its own risk model.

Phase 9 — Cross-read with the country assessments

ILAB's annual country reviews of government effort update between editions and tell you whether a listed origin is improving its legal framework, its inspectorate and its enforcement. That trajectory is what distinguishes a country worth engaging from one worth exiting, and the list alone cannot tell you which is which.

Phase 10 — Convert exposure into a decision, not a dashboard

For each flagged combination, decide what happens: enhanced supplier questionnaire, origin verification, third-party audit with an appropriate methodology, contractual remedy, or exit. A screen that produces a colour and no decision rule is theatre, and regulators reviewing due-diligence programmes have become adept at recognising it.

Phase 11 — Document the negative findings too

Record which combinations you screened and cleared, and on what basis. Due-diligence regimes increasingly require demonstrable process rather than demonstrable purity, and the evidence that you looked and reasoned is what protects a company that did the work and still had a problem.

Phase 12 — Re-screen on a calendar, not on an event

Set the next re-screen when the current one completes, tied to the expected publication cycle. This source degrades silently — nothing fails, the scores simply stop being true — and the only reliable defence is an obligation with a date on it.

The platform ships this as a step-checked workflow in playbooks.php, so progress is recorded against a case rather than held in someone’s head.

What to pair it with

No single source carries a finding. These are the datasets that corroborate, extend or contradict this one — and a source that contradicts is worth more than one that agrees, because it is the only thing that will tell you when you are wrong.

Source	Relationship	What it adds
ILAB findings on the worst forms of child labour	extends	Annual country assessments of government effort, with suggested actions. Updates between list editions and supplies the governance trajectory the list omits.
US customs forced labour enforcement	supersedes	Import-prohibition instruments that operate on specific goods and parties. Where an enforcement action exists, it displaces the list as the operative fact for a shipment.
UFLPA Entity List	extends	A US entity-level list creating a rebuttable presumption against specified parties and supply chains. This is where company-level exposure actually lives, and the List of Goods is not a substitute for it.
EU forced labour regulation	extends	The EU instrument prohibiting products made with forced labour on the Union market, which creates a second and differently designed enforcement regime that European sourcing must satisfy.
ILO forced labour standards	prerequisite	The international definitions against which ILAB assesses. Reading them is what makes the three finding categories precise rather than rhetorical.
ILAB comply chain guidance	extends	Practical guidance on constructing a social compliance system, which is the operational answer to a flag raised by the list.
Polaris typology research	corroborates	Business-model detail on how labour exploitation is organised, which converts a commodity-level flag into indicators visible in ordinary business records.
US State Department TIP Report	corroborates	Country-level assessment of anti-trafficking effort, providing an independent read on whether a listed origin has functioning enforcement.
Walk Free Global Slavery Index	contradicts	An estimative prevalence product built on different assumptions. Divergence between it and the list is usually informative about research access rather than about conditions.

Legal, ethical and operational constraints

The list is a research product with a statutory mandate, not a legal determination, and the distance between those two is the source of most legal risk in using it. It creates no prohibition, no presumption and no cause of action by itself. Acting adversely against a supplier solely because its country and commodity appear on the list — terminating a contract, publishing an allegation, filing a report naming them — is a claim you cannot support from this source alone and can attract defamation and contractual exposure in several jurisdictions. Conversely, ignoring the list is becoming legally untenable: mandatory human-rights due-diligence regimes in a growing number of jurisdictions require companies to identify and address risks in their chains, and a government-published list of exactly those risks is the first thing a regulator will ask whether you consulted. Where enforcement instruments exist — import prohibitions, entity lists, procurement restrictions — they carry real consequence and have their own evidentiary standards which the list does not satisfy. If your work will inform an adverse decision about a named party, get counsel involved early and build a separate evidentiary chain. Public submissions of evidence to ILAB are a legitimate route for material you cannot use directly.

Operational security

Fetching a public government report is unremarkable and needs no protection. The exposure in this workflow is commercial and human rather than technical. Supply-chain enquiries that reach into a producing region — approaching an exporter, commissioning a local audit, contacting workers or a union — are visible to the actors who benefit from the arrangement, and in some sectors those actors are willing to retaliate against local informants who have no protection at all. Plan any field-adjacent enquiry around the safety of the people who will be identified as having spoken, not around the confidentiality of your client. Internally, an unfinished supply-chain risk assessment is discoverable and commercially sensitive: a draft listing a client's suppliers as high risk, circulated widely and never resolved, is worse for that client than no assessment. Compartment drafts, resolve findings, and record the reasoning that closed each one.

Two rules that hold regardless of jurisdiction. Collection that is lawful is not automatically proportionate, and a dataset assembled for one purpose does not carry consent for another. Where the records concern identifiable people, the question is not only whether you may hold the data but whether holding it serves the purpose you are accountable for.

Is it earning its place?

Sources accumulate. Feeds get added during an incident and are never reviewed again, and a decade later the pipeline is carrying dead weight that nobody dares remove. These are the measures that show whether US DOL List of Goods (Child/Forced Labor) is contributing anything, and they are worth baselining now so the answer is available later.

Whether the edition year is recorded on every screen result in your system, and whether anything in production is still running against a superseded edition.
The proportion of flagged combinations that have a documented decision attached — verify, audit, remediate, exit — rather than only a score.
How many exposures were found by tracing inputs upward versus by screening finished products, which tells you whether your trace is doing any work at all.
Whether opaque sourcing jurisdictions are being recorded as unassessable rather than as low risk, checked by inspecting the bottom of your own risk ranking for countries that should not be there.
Time from publication of a new edition to completion of the re-screen, tracked as a service level rather than as an intention.
The share of your tariff mappings that carry a documented basis and a confidence value, since undocumented mappings are the part of your analysis most likely to be challenged.
Whether any adverse action against a named supplier has ever rested on this source alone, which should be zero.
Whether newly added pairs in the most recent edition were reviewed before they appeared in commercial risk products your competitors buy.

Beware of volume. Indicator counts rise easily and say almost nothing. Unique contribution — findings this source produced that no other source in your stack would have — is the measure that matters, and it is usually far lower than anyone expects.

Tradecraft notes

The distinctions that separate a competent analyst from a fast one:

The list is a prior, not a finding. It tells you the base rate for a commodity and origin; everything about a specific supplier has to be built separately and to a different standard.
Absence is the most misread feature of this dataset. A country with a short list may be well governed or may simply be closed to researchers, and distinguishing the two requires evidence from outside the list entirely.
Trace inputs, not products. The list sits upstream, so any screen applied at the finished-goods level will look reassuringly clean while the exposure sits two or three tiers back.
Keep ILAB's findings and your inferences visually distinct in every document you produce. The tariff mapping, the supplier attribution and the risk score are yours; only the pair and the finding are ILAB's, and a challenge will go straight to that boundary.
Read the country narrative for the entries that matter to you. It contains the production model, the region and the evidence base, all of which determine whether your supplier is plausibly implicated or plausibly nowhere near the problem.
The edition diff is the highest-value analysis and almost nobody does it. Additions represent evidence that has just become citable and a window before it propagates into everyone else's screening product.
Do not conflate the three findings. Import-enforcement regimes generally attach to forced labour specifically, so a child-labour-only entry has a different action set even though it may be morally comparable.
Delisting is about evidence, not absolution. Check whether the removal narrative describes verified reform or describes a research gap, and treat those two situations completely differently.
Submissions matter. ILAB takes evidence from the public, which means a well-documented finding from your own work can enter a national instrument — one of the few routes by which private research changes a government list.

Questions analysts actually ask

Does appearing on this list mean a specific company used forced labour?

No. The list operates at the level of a commodity and a country of production and names no company, facility or shipment. Company-level exposure requires an entirely separate evidentiary chain, usually built from customs records, corporate structure, facility-level reporting and field evidence. Treating the list as a supplier finding is both analytically wrong and legally exposed.

My supplier's country and commodity are not on the list. Are they clean?

You do not know. Listing depends on documented evidence, and documented evidence depends on researchers, unions and journalists having had access. Some of the most closed producing environments carry short lists for exactly that reason. Record such origins as unassessable rather than low risk, or your risk model will systematically reward opacity.

Where do the HS codes come from?

Not from the list. ILAB publishes tooling that maps listed goods to trade classifications, and you can build your own mapping, but either way it is an inference layered on top of the finding. One listed good can span many codes and one code can cover both listed and unlisted origins. Document the mapping and store it separately from ILAB's data.

How is this different from a customs import ban?

Completely different instruments. This list is a research product with no legal force of its own. Import-prohibition regimes act against specific goods and parties, require their own evidence, and carry real consequences at the border. Entity lists and procurement restrictions are different again. Only some of these can support an adverse decision, and knowing which is basic competence in this area.

How often does it update, and does that matter?

Roughly every two years, and it matters a great deal. Entries are added and removed each cycle, so a screening system built against an old edition will be wrong about specific countries and goods. Pin the edition, record its date, and schedule the re-screen when the current one finishes rather than waiting to notice a new publication.

An entry was removed. Has the problem been fixed?

Not necessarily. Removal means ILAB assessed the current evidence as no longer supporting the finding, which can happen because conditions genuinely improved or because the research that documented them stopped. Read the narrative accompanying the removal; it usually distinguishes the two, and the distinction should change your response entirely.

Can I use this to comply with European due-diligence law?

As an input, yes; as a compliance programme, no. European instruments require you to identify, prevent and address risks in your own chain and to document the process, which is a much broader obligation than screening against a US list. The list is good evidence that you consulted an authoritative source. It is not evidence that you did diligence.

Why is US production not covered?

Because the statutory mandate directs ILAB to report on goods produced abroad. It is a scope decision, not a finding about US conditions, and any presentation of the list as a global map of forced and child labour should say so explicitly. Domestic labour conditions are covered by other agencies under entirely different instruments.

What is the fastest way to get value from this source?

Diff the two most recent editions, take the additions, and check them against your supplier register and import records before they propagate into commercial risk products. That single exercise takes a day and typically surfaces exposure that a full screen against the whole list will bury under items you already knew about.

Standards, formats and interoperability

What this source speaks natively, and what it has to be translated into before a partner can consume it. Work that arrives in a recognised format is easier to defend, easier to hand over and easier to automate against:

ILO Conventions on the worst forms of child labour, minimum age and forced labour, which supply the international standards ILAB assesses against.
The Palermo Protocol definition of trafficking, which overlaps with but is not identical to the forced-labour finding used here.
Harmonised System tariff classification, which is how listed goods join to customs data — via a mapping you construct, not one the list supplies.
US Tariff Act import-prohibition provisions and the enforcement instruments built on them, which are the legally operative counterpart to this research product.
The EU forced labour regulation and national human-rights due-diligence statutes, which increasingly define what a company must do with a flag from this source.
OECD Due Diligence Guidance for Responsible Business Conduct, which supplies the process framework for turning a listed pair into a defensible programme.
UN Guiding Principles on Business and Human Rights, the framework against which corporate responses are judged by regulators and investors alike.
ISO country coding, used to join country entries to sanctions, trade and risk datasets without ambiguity.

References

Primary documentation and authoritative references for this source. Publishers revise and retire material, so treat the retrieval date as part of the citation and re-check before relying on any of it in a formal product.

List of Goods Produced by Child Labor or Forced Labor — US Department of Labor, Bureau of International Labor Affairs. The source itself: the entries, the methodology and the country narratives that make each finding interpretable.
Bureau of International Labor Affairs — US Department of Labor. The bureau, its mandate, and the full family of related products that are routinely confused with the main list.
Findings on the Worst Forms of Child Labor — US Department of Labor. Annual country assessments of government effort, which update between list editions and supply the reform trajectory.
Comply Chain — US Department of Labor. ILAB's guidance on building a social compliance system — the operational answer to a flag rather than another flag.
Forced labour enforcement — US Customs and Border Protection. The import-prohibition regime that carries actual legal consequence, and the boundary the list does not cross.
UFLPA Entity List — US Department of Homeland Security. Where entity-level exposure actually lives in the US system, and the correct reference when a company-level question is asked.
Regulation (EU) 2024/3015 on prohibiting products made with forced labour — European Union. The EU market-prohibition instrument, which creates a second regime with its own evidentiary and procedural design.
Forced labour, modern slavery and human trafficking — International Labour Organization. The international standards and definitions underpinning the findings, and the global estimates for context.
Trafficking in Persons Report — US Department of State. Country-level assessment of anti-trafficking effort, for reading a listed origin's enforcement capacity.
The Typology of Modern Slavery — Polaris. Business-model detail that turns a commodity-level flag into indicators observable in ordinary commercial records.

Link integrity: every reference above was verified with a live request when this page was generated. Where a publisher had moved or withdrawn a document, the link was repointed at a preserved copy in the Internet Archive and marked as archived. Anything with no reachable copy anywhere had its link removed rather than left to rot — the source is still credited, it simply cannot be linked.

Put it into practice

The Quantus Intel threat intelligence platform operationalises this source: it ingests each edition as a versioned set of good-country findings, diffs editions to surface new entries as events, keeps your tariff mapping as a labelled inference layer rather than a fact, and joins the result to supplier registers and enforcement actions across `correlate.php`, `sanctions.php` and `financial-crime.php`.. Browse the full source catalogue, or follow any tag above into the rest of the library.