Hidden Narratives in Public Life: 7 Ways to Spot & Disrupt — Through Iblis’s Eyes

This article explains how hidden narratives in public life are created, funded, and spread — and shows ordinary readers how to spot, measure, and disrupt them. Using three case studies from the Through Iblis’s Eyes series —drawn from Iblis’s strategies throughout scripture and human history, you’ll get a 12-point quick scan, a reproducible 30-day News-Diet experiment, a 30-day Narrative Audit (with CSV templates), and ready-to-post counter-frames and scripts you can use in communities, newsroom threads, or civic campaigns.

Hidden narratives in public life change what communities fear, who they blame, and which solutions feel inevitable. This investigative post maps how those narratives are seeded, amplified, and institutionalized — then gives two reproducible experiments (a 30-day News-Diet and a 30-day Narrative Audit) plus measurement templates so readers can test and publish results.

Practical, faith-aware, and evidence-focused: case studies, CSV trackers, a how-to checklist, and ready-made social scripts are included so you can act — not just diagnose. Understanding hidden narratives in public life is the first step toward reclaiming civic conversation.

Why Hidden Narratives in Public Life Matter

Every day a repeated phrase narrows what we imagine is possible — and that narrowing is often invisible. Hidden narratives in public life make fear feel normal and forgiveness rare; this post is a practical attempt to tear those lenses off so communities can choose freely again.

“Whoever among you sees an evil action, let him change it with his hand; if he is unable, then with his tongue; and if he is unable, then with his heart—and that is the weakest of faith.”

Sahih Muslim, (The Book of Faith, Hadith Number 49)

Hidden narratives matter because they shape agendas before facts do ^{[2] [3]} . A well-placed frame can make a technical budget cut read like a moral imperative; a repeated euphemism can convert exclusion into “efficiency.” Two modern examples: a municipal debate framed as “budget realism” that quietly normalizes youth program cuts (local; see Case Study A), and a viral short video that seeds a fear frame later echoed by national commentators (global; see Case Study C). These narratives change policy windows and social tolerances long before parliamentary votes or official reports catch up.

The anatomy of a narrative

Once you see the moving parts, the fear loses its mystique. Hidden narratives in public life always follow a small logic: seed, frame, euphemism, carrier, spectacle — and each can be pulled apart ^[4]. This anatomy section shows the common mechanics that make hidden narratives in public life persist.

Uqbah bin ‘Amir states: “The Messenger of Allah {ﷺ} commanded me to recite {Al-Mu’awwidhatayn} after every obligatory prayer.”

Sunan an-Nasa’i, (The Book of The Commencement of the Prayer, Hadith Number 1336)

Narratives travel along predictable parts:

Mini glossary: Seed / Frame / Carrier / Anchor (recurring metaphor). ^[5]

Case Study A — Establishing a culture that permits the Other

The first time someone calls a neighbor a “cost,” something inside a community shifts; empathy thins. Hidden narratives in public life do this slowly — one dehumanizing phrase at a time — and this case shows how.

(Context & summary — what the analysis claims)
In these case studies we track how hidden narratives in public life move from private talks to public policy. The selected analysis argues that a sustained rhetorical pattern has normalized dehumanization of a target group by repeatedly describing them as a cultural or security burden. The review maps recurring metaphors (e.g., “invasion,” “cost”), notes selective use of statistics, and highlights policy proposals framed as “necessary sacrifices” ^[6]. The aim is not to litigate any single factual claim but to show how linguistic strategies shift public sense of what is acceptable to readers and civic commentators.

Timeline (annotated)

• Seed (T0) — earliest articulated claim (e.g., a talk or op-ed framing the group as “unsustainable”).
• Echo (T0+3–6 months) — local blogs and niche outlets repeat the frame with slight variations.
• Carrier engagement (T0+6–12 months) — think-tank report reframes issues with selective metrics.
• Mainstreaming (T0+12–24 months) — mainstream outlets repeat the solution language; policymakers adopt “cost-saving” frames in committee hearings. ^{[7] [8]}
• Institutional uptake (T0+24–36 months) — policy language reflects the euphemism; programs shrink or oversight weakens.

Frame audit (mini table)

Pull-quotes (3 items with source excerpts)

• “We cannot afford to sustain this… it’s unsustainable” — [excerpt source].
• “They change the character of our spaces” — [excerpt].
• “The only real choice is to prioritise what remains” — [excerpt].

Counter-frame paragraph:
Framing social services as a moral investment reframes the debate: rather than “affordability,” we should ask, “what future costs does removing support impose?” Evidence shows investments in youth and inclusion reduce long-term fiscal and social costs; a humane accounting treats community resilience as prevention rather than discretionary spending. Use the frame audit to see how hidden narratives in public life reframe ordinary budget choices as moral imperatives.

Measurement suggestions (how to test diffusion locally)

• Run the Narrative Audit for 30 days (one headline a day; log frames).
• Track the euphemism’s repetition across outlets (count occurrences weekly).
• Correlate changes in public opinion (local poll, even a 100-person sample) against frequency of the euphemism.

Disclaimer: This article analyses public narratives; readers should consult primary sources and verify claims.

Case Study B — Secret organizations & opacity

When language is refined behind closed doors, the public only sees the polished result — and tends to accept it ^[9]. Hidden narratives in public life often begin in secrecy; this case traces how that solitude turns into public authority. Local watchdogs should prioritize tracing funding when investigating hidden narratives in public life.

(Network map & funding trace approach)
This case study traces a narrative that begins in closed networks (private lectures, gated conferences, white papers) and later appears in public policy language. Map nodes: closed forums → intermediary think-tanks → opaque donors → policy champions ^[10]. The key analytic move is to follow funding chains and repeated author names.

Who benefits? Actor analysis

• Direct beneficiaries: organizations gaining legitimacy (policy outcomes, contracts).
• Indirect beneficiaries: donor networks that prefer low-visibility influence.
• Amplifiers: sympathetic journalists and niche platforms who translate internal language for public audiences.

Trace notes (who said what first)

• Identify earliest white paper or lecture. Quote the opening claim and timestamp or date. Archive the page or screenshot. Use registries to check organizational funding.

Practical FOI / registry steps (how a reader or journalist can trace funding)

1. Search national NGO and charity registries for named organizations.
2. Use corporate registries to find directors and donors.
3. File FOI requests for grants to public institutions (template below).
4. Check tax filings (where public) and grant databases (e.g., OpenSecrets / ProPublica for U.S. contexts). ^{[11] [12]}

Short FOI template letter (copy-ready):

Dear [FOI Officer],
Under [relevant FOI law], please provide copies of all grant agreements, tender documents, and correspondence mentioning [Organization X] between [start date] and [end date]. Please include donor names, amounts, and contract scopes. If any information is withheld, provide the legal basis for withholding.
Sincerely, [Name]

Recommendation for civic watchdogs
Set up a simple tracker that flags names that appear in both closed and public documents. Publicize overlaps with source links and invite crowdsourced verification. Tracing funding and speaker lists helps reveal how hidden narratives in public life are seeded within closed networks. ^[13]

Case Study C — Viral spectacle & myth lifecycle

A single vivid clip can lock a whole belief in place; can exert persuasive power that statistics alone seldom do ^[14]. The heart remembers what the brain later rationalizes. Hidden narratives in public life use spectacle to make forgetfulness and haste feel like conviction.

(Anatomy of a viral narrative)
Short viral pieces rely on emotional hooks (shock, anger, moral outrage), compressed evidence cues (an image + sentence), and repeated tropes that exploit cognitive shortcuts (availability bias, emotional contagion) ^[15]. Viral narratives become durable when the spectacle attaches to institutional language later, See: framing theory (Entman, 1993).

Lifecycle diagram (seed → peak → institutional adoption)

• Seed: short clip or provocative image with a bold claim.
• Peak: wide shares, influencer pickups, trending tags. ^[16]
• Consolidation: mainstream commentary and fact-light op-eds.
• Adoption: policy actors reference the viral frame or policymakers use expressive language originally popularized in the viral piece.

Pre-bunk script:

Short pre-bunk (tweet/post): “Headline: [X]. Quick check: Where’s the evidence? I can’t find the original data. Let’s wait for a primary source before resharing.”

Longer pre-bunk (thread):

• 1) State the claim;
• 2) point to the missing evidence;
• 3) offer a plausible alternative frame (e.g., “data gaps, not conspiracy”);
• 4) invite readers to the source documents.

Pre-bunk and inoculation messages are effective against emerging hidden narratives in public life when deployed early. When a clip goes viral, remember that hidden narratives in public life often piggyback on emotional shortcuts rather than evidence. ^[17]

Two scripts for community leaders

• Short (30–40 words): “I saw a viral clip claiming X. The claim matters — but the evidence is missing. Let’s pause and verify before acting.”
• Long (120–180 words): Provide context, summarize what’s known, explain the potential harm of believing an unverified claim, and offer a single concrete action (e.g., “we’ll hold a community briefing with primary documents”).

How to measure virality decay after correction
Track share counts or mentions for 7–14 days pre- and post-correction. Measure engagement change (shares, replies) and sentiment shift (quick manual coding or a small sample). For deeper network-level analysis and policy recommendations, see extended analyses of networked propaganda. ^[18]

How to spot hidden narratives (checklist + annotated examples)

Once you learn the signals, the work of seeing becomes an act of care. Hidden narratives in public life hide in our rush; the checklist is a breath that lets us choose differently. For faith-aware moderators and community leaders, our short primer on coping with doubt in Islam offers compassionate scripts for addressing rumor, fear, and communal anxiety when correcting narratives.

Seven ways to spot & disrupt hidden narratives

“Whoever among you sees an evil action, let him change it with his hand; if he is unable, then with his tongue.”

Sahih Muslim, (The Book of Faith, Hadith Number 49)

This checklist highlights the signs that usually accompany hidden narratives in public life:

1. Trace the source (find the seed).
   Action: run a quick quotation search for the earliest appearance of the phrase; archive the first public instance. (See: Case Study B — Network map & funding trace; use the FOI template and origin tracing steps.)
2. Test the language (euphemism & label test).
   Action: translate every loaded term into plain language and flag euphemisms that hide moral choices. (See: Case Study A — Frame audit; Checklist items: Euphemism test & Frame test.)
3. Measure repetition (who repeats it, how often).
   Action: log occurrences across outlets for 30 days (use narrative_audit.csv) and chart carrier frequency. (See: Narrative Audit instructions and Measurement templates.)
4. Expose carriage (map the carriers).
   Action: build a simple node map (closed forum → think-tank → outlet → influencer) and publish it with source links. (See: Case Study B — Carrier & funding map.)
5. Pre-bunk before it peaks.
   Action: when a viral anchor appears, circulate a one-page context packet and an inoculation message before the clip fully circulates. (See: Case Study C — Pre-bunk script and the pre-bunk templates.) ^[19]
6. Publish counter-frames with evidence.
   Action: write a concise counter-frame paragraph, publish it with one primary source, and ask three local partners to share it within 48 hours. (See: Counter-frame paragraph (Case Study A) and Counter-Frame Publishing Protocol.)
7. Demand institutional transparency and remediate harms.
   Action: file FOI/registry checks for policy language uptake, publish overlaps, and propose remediation steps (retractions, funded repair). (See: Seerah governance lessons, FOI template, and watchdog recommendations.)

Quick how to use this list: run items 1–4 to diagnose the narrative; run items 5–7 to intervene and measure impact. Each step links directly to the case studies, templates, and CSV trackers provided in this article. Faith-based communities can use the short pre-bunk scripts to counter hidden narratives in public life respectfully.

12-item checklist (quick-scan)

1. Who benefits? — Identify likely beneficiaries.
2. First appearance — Trace earliest public iteration.
3. Repetition pattern — How often/how fast does the phrase repeat?
4. Euphemism test — Translate the term into plain language.
5. Frame test — Map problem / actor / moral language / solution.
6. Funding trace — Any opaque funding or donors?
7. Actor overlap — Same names across platforms?
8. Evidence gap — Claims made without verifiable facts?
9. Emotional hook — Dominant emotion the narrative activates.
10. Correction resistance — Do corrections stick, or does the narrative reappear? ^[20]
11. Institutional uptake — Are formal actors using the same language?
12. Counter-frame feasibility — Can an alternative frame replace it?

One-minute test (you can run now)
Pick a headline. Ask: Who benefits? Is there a euphemism? Is there a direct source link? If two of these fail, flag it for a Narrative Audit entry. When running the one-minute test you should ask whether hidden narratives in public life are being masked by euphemism. ^[21]

Two experiments you can try (News-Diet + Narrative Audit)

Experiments are courage in action — small changes that test whether we are being shaped or can shape back ^[22]. Hidden narratives in public life are weakened by disciplined curiosity and collective documentation. If you’re running a community workshop, use the facilitator notes in Dealing with doubts in Islam for roleplay prompts and respectful correction techniques that avoid amplifying spectacle.

“It is enough of a lie for a man to narrate everything he hears.”

Sahih Muslim, (The Book of Faith, Hadith Number 5)

News-Diet experiment (30 days)

Changing what you consume rewires habit and outrage; a calmer attention economy resists spectacle ^[23]. Hidden narratives in public life lose power when the audience chooses depth over speed.

The News-Diet is intentionally designed so participants can step back and notice hidden narratives in public life without amplifying them. Logging headlines daily is how communities can map and measure hidden narratives in public life over time.

Protocol:

• Limit short-form feeds (TikTok/Threads/short clips) to 25–30 minutes/day. ^[24]
• Replace 20 minutes/day of short-form with long-form reading (in-depth articles, reports).
• Log daily in news_diet.csv (headers provided below).

Metrics: short-form minutes/day, long-form minutes/day, clarity rating (1–10), number of corrected shares, subjective cognitive load.

Output: After 30 days write a 600–800 word findings post and upload the CSV.

Narrative Audit (30 days)

Small acts of documentation are public medicine; each logged headline is an inoculation against mass forgetfulness. Hidden narratives in public life dissolve when their patterns are made visible. Logging headlines daily is how communities can map and measure hidden narratives in public life over time.

Protocol:

• Each day pick one headline or short clip.
• Fill a row in narrative_audit.csv with structured fields (headers below).
• Write one counter-frame paragraph for that headline and attempt one share (reply, tweet, community post).

Metrics: days completed, top 3 frames identified, adoption_count (how many peers used your counter-frame), average engagement on counter-posts.

Output: A compiled analysis post that lists top frames, sample counter-frames, and lessons learned. Publish your CSVs so others can verify patterns and test whether hidden narratives in public life are local or part of larger campaigns.

Measurement templates

The measurement templates let volunteers quantify the spread of hidden narratives in public life over time. Data frees conversation from anecdote. If you publish your rows, others can test your claims and help repair the public square ^[25]. Hidden narratives in public life become researchable rather than inevitable.

Download the experiment tracker: CSV + Google Sheet template. Make a copy, log one row per day, and publish a 30-day findings post. Example rows are shown below to help you get started:

Measurement Templates - Hidden Narratives in Public Life

1 file(s) 0.62 KB

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Narrative Audit

Prior exposure can make false claims feel familiar and therefore accurate ^[26]. Narratives stick because of confirmation bias, motivated reasoning, and social identity dynamics. ^[27] Use the Narrative Audit CSV to log every instance of hidden narratives in public life you find.

News Diet

Our 30-day experiments test whether individuals can disrupt hidden narratives in public life through simple routines.

Four applied governance lessons from the Seerah

The Seerah offers governance practices that heal narrative harms: verification, patience, consultation, and restoration. Hidden narratives in public life can be countered by processes that restore dignity and evidence. The Seerah lessons in this post explain governance responses to hidden narratives in public life. If you want the Seerah lessons in a broader, practice-first form, see islamic instruction manual for living, which maps scripture to everyday governance and community remediation.

“The best of people are those who are most beneficial to people.”

Al-Mu’jam Al-Awsat of At-Tabarani, (Hadith Number 5787)

These governance lessons are practical ways to repair harms caused by hidden narratives in public life:

1. Ifk & evidentiary safeguards: The Ifk episode (false accusation) shows the damage of rumor; governance needs fast, public evidentiary processes and transparent investigation timelines to prevent rumors from hardening into policy. ^[28]
2. Consultation (Shura) & plural input: Incorporate broad, documented consultation mechanisms before adopting urgent language that affects rights. Publish minutes and dissenting views.
3. Chain of testimony (Isnad) for narratives: Require transparent sourcing for public claims (who said what, when, and with what evidence), and make those archives searchable.
4. Community remediation & rehabilitation: When narratives cause harm, design public remediation (retractions, funded restorative programs) and measure impact over time.

Each lesson maps to a practical change: mandatory source disclosure in official statements, FOI-friendly funding registries, rapid response correction teams in public agencies, and community audit requirements for policy memos. ^[29]

Conclusion — what to do right now (practical checklist)

The smallest practical acts — a logged headline, a shared counter-frame, a published CSV — are how public life is rebalanced. Hidden narratives in public life yield to patient, documented action.

“A person’s feet will not move on the Day of Resurrection until he is asked about five things: about his life and how he spent it; about his youth and how he used it; about his wealth, how he earned it and how he spent it; and about his knowledge, and what he did with it.”

Jami’ at-Tirmidhi, (The Book on the Description of the Day of Judgment, Hadith Number 2416)

Five-step checklist (immediate)

1. Start a 7-day mini Narrative Audit — one headline per day; log in narrative_audit.csv.
2. Begin a 30-day News-Diet — set a daily timer: 25 minutes short-form, 20 minutes swapped for long reads. Record in news_diet.csv.
3. Publish one counter-frame from your audit and tag three local collaborators.
4. Run a funding name check: search the registry for any recurring actor names across your audit rows.
5. Share raw CSV (anonymized) and invite peer verification.

Publish your 30-day report in the comments below (paste a 1–3 sentence findings summary + a public CSV link) or email your tracker using the [Contact Form]. I’ll curate the most rigorous audits into a public roundup and feature standout contributors. Crowdsourced audits scale — your data helps other communities spot and disrupt hidden narratives in public life. When you prepare community briefings or public Q&A, share the linked checklist Respectful Questions to Ask About Islam to keep conversation factual, measured, and respectful.

When assessing a headline, ask if it fits patterns we’ve seen in hidden narratives in public life.

FAQs

References

1. Pennycook, G., & Rand, D. G. (2019). Fighting misinformation on social media using crowdsourced judgments of news source quality. Proceedings of the National Academy of Sciences, 116(7), 2521–2526. https://doi.org/10.1073/pnas.1808645116 ↩︎
2. Entman, R. M. (1993). Framing: Toward clarification of a fractured paradigm. Journal of Communication, 43(4), 51–58. https://doi.org/10.1111/j.1460-2466.1993.tb01288.x ↩︎
3. McCombs, M. E., & Shaw, D. L. (1972). The agenda-setting function of mass media. Public Opinion Quarterly, 36(2), 176–187. https://doi.org/10.1086/267990 ↩︎
4. Benford, R. D., & Snow, D. A. (2000). Framing processes and social movements: An overview and assessment. Annual Review of Sociology, 26, 611–639. https://doi.org/10.1146/annurev.soc.26.1.611 ↩︎
5. Vosoughi, S., Roy, D., & Aral, S. (2018). The spread of true and false news online. Science, 359(6380), 1146–1151. https://doi.org/10.1126/science.aap9559 ↩︎
6. Lakoff, G. (2004). Don’t Think of an Elephant!: Know Your Values and Frame the Debate. Chelsea Green Publishing. https://www.chelseagreen.com/product/dont-think-of-an-elephant-know-your-values-and-frame-the-debate/ ↩︎
7. Allcott, H., & Gentzkow, M. (2017). Social media and fake news in the 2016 election. Journal of Economic Perspectives, 31(2), 211–236. https://doi.org/10.1257/jep.31.2.211 ↩︎
8. Allcott, H., & Gentzkow, M. (2017). Social media and fake news in the 2016 election. Journal of Economic Perspectives, 31(2), 211–236. https://doi.org/10.1257/jep.31.2.211 ↩︎
9. Benkler, Y., Faris, R., & Roberts, H. (2018). Network Propaganda: Manipulation, Disinformation, and Radicalization in American Politics. Oxford University Press. https://doi.org/10.1093/oso/9780190923214.001.0001 ↩︎
10. Bradshaw, S., & Howard, P. N. (2018). A Global Inventory of Organized Social Media Manipulation. Oxford Internet Institute, University of Oxford. https://demtech.oii.ox.ac.uk/wp-content/uploads/2018/07/A-Global-Inventory-of-Organized-Social-Media-Manipulation.pdf ↩︎
11. OpenSecrets. (n.d.). Dark Money & Funding Transparency. Center for Responsive Politics. Retrieved December 13, 2025, from https://www.opensecrets.org/dark-money ↩︎
12. ProPublica. (n.d.). Investigations & Dark Money Project. Retrieved December 13, 2025, from https://www.propublica.org/series/dark-money ↩︎
13. Woolley, S. C., & Howard, P. N. (2018). Computational Propaganda. Oxford University Press. https://doi.org/10.1093/oso/9780190858165.001.0001 ↩︎
14. Green, M. C., & Brock, T. C. (2000). The role of transportation in the persuasiveness of public narratives. Journal of Personality and Social Psychology, 79(5), 701–721. https://doi.org/10.1037/0022-3514.79.5.701 ↩︎
15. Bakir, V., & McStay, A. (2018). Fake news and the economy of emotions. Digital Journalism, 6(2), 154–175. https://doi.org/10.1080/21670811.2017.1348889 ↩︎
16. Tufekci, Z. (2017). Twitter and Tear Gas: The Power and Fragility of Networked Protest. Yale University Press. https://yalebooks.yale.edu/book/9780300215111/twitter-and-tear-gas/ ↩︎
17. Lazer, D. M. J., Baum, M. A., Benkler, Y., Berinsky, A. J., Greenhill, K. M., Menczer, F., … & Zittrain, J. L. (2018). The science of fake news. Science, 359(6380), 1094–1096. https://doi.org/10.1126/science.aao2998 ↩︎
18. Benkler, Y., Faris, R., & Roberts, H. (2020). The Rise of Networked Propaganda — extended analyses and follow-up. Berkman Klein Center for Internet & Society, Harvard University. https://cyber.harvard.edu/story/2020-03/rise-networked-propaganda-extended-analyses-and-follow ↩︎
19. Roozenbeek, J., & van der Linden, S. (2019). Fake news game confers psychological resistance against misinformation. Palgrave Communications, 5(1), 65. https://doi.org/10.1057/s41599-019-0279-9 ↩︎
20. Nyhan, B., & Reifler, J. (2010). When corrections fail: The persistence of political misperceptions. Political Behavior, 32(2), 303–330. https://doi.org/10.1007/s11109-010-9112-2 ↩︎
21. Guess, A., Nyhan, B., & Reifler, J. (2018). Selective exposure to misinformation: Evidence from the consumption of fake news during the 2016 U.S. presidential campaign (No. w24737). National Bureau of Economic Research (NBER). https://www.nber.org/papers/w24737 ↩︎
22. Pennycook, G., & Rand, D. G. (2019). Fighting misinformation on social media using crowdsourced judgments of news source quality. Proceedings of the National Academy of Sciences, 116(7), 2521–2526. https://doi.org/10.1073/pnas.1808645116 ↩︎
23. Bakir, V., & McStay, A. (2018). Fake news and the economy of emotions. Digital Journalism, 6(2), 154–175. https://doi.org/10.1080/21670811.2017.1348889 ↩︎
24. Bakshy, E., Messing, S., & Adamic, L. A. (2015). Exposure to ideologically diverse news and opinion on Facebook. Science, 348(6239), 1130–1132. https://doi.org/10.1126/science.aaa1160 ↩︎
25. Shiller, R. J. (2017). Narrative economics. American Economic Review, 107(4), 967–1004. https://doi.org/10.1257/aer.107.4.967 ↩︎
26. Pennycook, G., Cannon, T. D., & Rand, D. G. (2018). Prior exposure increases perceived accuracy of fake news. Journal of Experimental Psychology: General, 147(12), 1755–1770. https://doi.org/10.1037/xge0000465 ↩︎
27. Ecker, U. K. H., Hogan, J. L., & Lewandowsky, S. (2022). The psychological drivers of misinformation belief and its resistance to correction. Nature Reviews Psychology, 1(4), 183–195. https://doi.org/10.1038/s44159-022-00030-y ↩︎
28. Herman, E. S., & Chomsky, N. (1988). Manufacturing consent: The political economy of the mass media. Pantheon Books. https://openlibrary.org/works/OL31013W/Manufacturing_consent ↩︎
29. OECD. (2020). Governance Responses to Disinformation: A Multi-Country Review. OECD Publishing. https://doi.org/10.1787/40e87178-en ↩︎
30. European Parliament / EU. (2021). Policy toolkits & governance guidance on disinformation. (Reports / syntheses). https://www.europarl.europa.eu/RegData/etudes/STUD/2021/690022/EPRS_STU(2021)690022_EN.pdf ↩︎