Melissa Brown Blaeuer and Pamela Fadden for Assembly
WE THE PEOPLE representation for Butler North Caldwell West Caldwell Fairfield Jefferson Kinnelon Lincoln Park Morris Plains Montville Parsippany-Troy Hills Rockaway Township Verona West Milford
We are proud of this endorsement. The public trust is more important now than ever! * * * * "The Good Government Coalition of New Jersey (GGCNJ) is a nonpartisan, grassroots group whose mission is to strengthen democracy by working with residents across our state to bring greater transparency, accountability, and participation to our state and local governments." Here’s why we enthusiastically endorse Melissa Brown Blaeuer for LD26 Assembly https://www.ggcnj.org/endorsements2021/brownblaeuer2021/ Here’s why we enthusiastically endorse Pamela Fadden for LD26 Assembly https://www.ggcnj.org/endorsements2021/pamelafadden2021/
↗ View in Meta Ad Library (the live creative — image/video/layout)
| Overall score | 40.0/100 |
| Spend / Reach / Long. / Eff. | 30.5 · 66.9 · 1.1 · 61.6 |
| Spend range | USD 800–899 |
| Impressions | 35,000 – 39,999 |
| CPM (≈ $/1k impr) | USD 22.65 |
| Est. audience size | 100,001 – 500,000 |
| Days live | 5 (2021-10-28 → 2021-11-02) |
| Created | 2021-10-28 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | VA — Pamela Brown |
| Surfaced by | “senate:Pamela Brown” |
| Issue | democracy elections |
| Framing | positive candidate |
| Message type | persuasion |
| Emotional appeal | pride |
| Production tier | semi pro |
| Who pictured | none |
| Symbols | none |
| Call to action | learn more |
| Standout element | Removed-content placeholder card revealing ad was flagged for policy non-compliance, framing the candidates as victims of censorship |
| Tactic | The ad leverages a nonpartisan good-government endorsement to build credibility and signal integrity, appealing to reform-minded voters who value transparency and accountability. |
| New Jersey | 99.8% |
| New York | 0.2% |
| Unknown | 0.0% |
| 65+ · unknown | 0.1% |
| 25-34 · female | 25.7% |
| 65+ · male | 3.1% |
| 35-44 · male | 4.3% |
| 55-64 · female | 5.9% |
| 25-34 · male | 10.2% |
| 25-34 · unknown | 0.2% |
| 65+ · female | 5.9% |
| 45-54 · male | 2.8% |
| 18-24 · unknown | 0.2% |
| 55-64 · male | 2.9% |
| 45-54 · female | 6.3% |
| 35-44 · female | 12.2% |
| 18-24 · male | 7.1% |
| 45-54 · unknown | 0.1% |
| 55-64 · unknown | 0.1% |
| 35-44 · unknown | 0.2% |
| 18-24 · female | 12.9% |