57,274 is a sum, not a headline.
Every impression comes from one of three platform dashboards. Add the three authoritative platform totals and you get the figure, no rounding, no estimation on top.
Three platforms, three different meters.
These are not the same metric relabelled. Each platform measures reach its own way; we take each at its dashboard-authoritative value and are explicit about what it means, and we deliberately deflate the Instagram figure to avoid double-counting.
The number of times campaign content appeared on screen. Taken directly from the chapter-level dashboard for each custom date range. Authoritative, not estimated.
The number of times content was displayed in feeds. Taken from the LinkedIn analytics dashboard per chapter window. Reach ("members reached") is reported separately and never summed, because it deduplicates people.
Total views minus "From Other", the cross-post referral traffic that flows FB → IG. Subtracting it removes reach already counted on Facebook, so the same view is never counted twice. For Reels, the FB-reported "Instagram views" is used as the subtraction value and cross-validates exactly in three chapters.
Why Instagram is the only adjusted number
Facebook and LinkedIn are reported exactly as their dashboards show them. Instagram is the one platform where cross-posting could inflate the total, so it is the one number we reduce, the conservative choice. The full per-post subtraction is in the dataset.
Where the reach came from.
The campaign ran as nine units (six chapters, a special report, a launch, and a close) alternating Bangladesh and United States themes. This shows how reach distributed across them (chapter-dashboard figures; the launch post is nested inside Chapter 1).
| Unit | Theme · country | 3-platform | |||
|---|---|---|---|---|---|
| Chapter 1 | Investment in public health · BD | 12,775 | 2,922 | 1,152 | 16,849 |
| Chapter 2 | Medical-debt crisis · US | 4,712 | 1,282 | 929 | 6,923 |
| Chapter 3 | Michigan health policy · US | 3,877 | 1,565 | 1,221 | 6,663 |
| Special Report | Bengal Basin earthquake · BD | 2,190 | 1,013 | 562 | 3,765 |
| Chapter 4 | Private-healthcare literacy · BD | 3,547 | 1,910 | 877 | 6,334 |
| Chapter 5 | Health communication · US | 1,632 | 1,240 | 1,363 | 4,235 |
| Chapter 6 | Workforce crisis · US | 5,187 | 1,529 | 877 | 7,593 |
| Season Closing | Bi-national reflection | 1,815 | 903 | 76 | 2,794 |
| Chapter-level sum | 35,735 | 12,364 | 7,057 | - | |
| Full-campaign dashboard lock (headline) | 36,997 | 13,054 | 7,223 | 57,274 | |
The parts reconcile to the whole, to within a few percent, and we say why.
Adding the individual chapter dashboards gets you very close to the full-campaign dashboard, but not to the exact digit. That small gap is expected in honest manual tracking, and here is precisely how large it is and what causes it.
Why a 3-5% residual exists, and why it's a feature, not an error
This campaign was tracked by hand across three platforms over eight weeks from native dashboard screenshots, with no API aggregation tool. Dashboards attribute traffic differently at the whole-campaign level than at the individual-post level. The residual comes from:
- Post lifetime accrual: algorithmically promoted posts kept gathering views after their chapter window closed.
- Reshares and profile discovery attributed at the page level, not to any single post.
- Window-boundary gaps between one chapter's date range and the next's.
- Hashtag and keyword tails from #HealthSystemResilience and related tags.
The full-campaign dashboard figures are the authoritative headline; the chapter sums are a secondary validation view. A 96.6% reconciliation on manual tracking supports the integrity of the method without requiring the sub-sums to match to the digit.
Manually, by one person, with the receipts kept.
Every figure was captured from the platforms' own native dashboards (the Meta Professional Dashboard for Facebook, LinkedIn Analytics for LinkedIn, and per-post insights for Instagram) via manual screenshots taken at the end of each chapter and again on a lifetime review, typically two to fourteen days after publication. No third-party analytics or API aggregation tool was used. This was a solo-practitioner campaign with a $0 advertising budget over an eight-week window, which is also why any comparison to published industry benchmarks (built on funded, multi-person organizational accounts) is a conservative one.
Read honestly.
The limits we want you to know
- Impressions and views are not unique people. One person can be reached several times; 57,274 is total reach across platforms, not 57,274 distinct individuals.
- The three metrics are not identical. Facebook "views," LinkedIn "impressions," and Instagram "native views" measure related but different things; the total is a cross-platform reach indicator, not a single deduplicated count.
- These are the platforms' own estimates. They are taken from native dashboards and have not been independently audited by a third party. What we can show is that every number traces to a dated dashboard and a documented rule.
- The Instagram figure is calculated not read directly, using the subtraction method above, a deliberately conservative choice, but a modeled one.
Quick answers.
How is the 57,274 figure calculated?
It is the sum of three platform dashboards over Feb 21, Apr 12, 2026 at zero ad spend: 36,997 Facebook views, 13,054 LinkedIn impressions, and 7,223 Instagram native views.
Are the numbers independently verifiable?
Every figure traces to the platforms' own native dashboards and a documented calculation rule, and the full post-level dataset is downloadable below. Platform analytics are the platforms' own estimates and are not third-party audited.
What counts as an "impression"?
Each platform measures differently: Facebook "views," LinkedIn "impressions," and Instagram "native views" (total views minus cross-post referral traffic). The total is a cross-platform reach indicator, not a count of unique individuals.
Why don't the chapter totals add up to exactly 57,274?
Adding the individual chapter dashboards reconciles to 96.6% of the full-campaign Facebook total and 94.7% of LinkedIn. The 3-5% residual comes from post lifetime accrual, reshares, and hashtag discovery, a known, documented feature of manual native-dashboard tracking.
The full dataset is public.
Every figure on this page traces to a single source file: a post-level master dataset with each of the ~40 cascade posts, per-platform metrics, the reconciliation tab, the full methodology rules, country distribution, and APA references.
HSR Season 1, Master Dataset (.xlsx)
12 tabs · post-level detail for Facebook, LinkedIn & Instagram · dashboard-vs-sum reconciliation · calculation rules · country distribution · references.
Prepared as the HLED 695 capstone deliverable, April 2026. The headline figures (36,997 Facebook / 13,054 LinkedIn / 276 LinkedIn social engagements) are the platform-dashboard authoritative numbers; Instagram native views are calculated post-by-post as described above.
Licensed under Creative Commons Attribution 4.0 (CC BY 4.0), free to reuse, including commercially, with attribution to HSREP (Md Shafaat Ali Choyon).