TERFs: The Insurance Fraudsters Of Feminism
You know the ones. They pretend you hit them in your car by jumping on your hood while you are moving slow and pretend to have an injury so that they can claim on insurance. Pay them attention and they will have gotten their way. TERFs work in exactly the same way. They will bait people or organizations into a reaction and then use that to play the victim and continue their baseless claims. So how do you solve a problem like TERFs? You ignore them. I know, I know, this whole site is here to call them out, but it’s also here to archive the things they say to pass on to future venues, to give them the full picture of the people they are booking. I myself am also guilty of playing into their hands. But it needs to stop. What made me come to this realization? Two
The Source Summary reproduces the first 150 words of the source article unless a Collective editor has explicitly locked a replacement.
Why this article may matter
Community significance
“TERFs: The Insurance Fraudsters Of Feminism” may matter to community readers because it preserves a first-person or testimonial account connected to feminism and gender politics, while also engaging history, archives, and memory. Such accounts can document how an issue was understood and experienced from within the period or community being discussed.
Historical significance
The article may have historical value because it explicitly interprets or preserves material concerning feminism and gender politics. Published in 2013 by The TERFs, it can be read both for the history it describes and as evidence of how history, archives, and memory was framed at that moment.
Policy significance
“TERFs: The Insurance Fraudsters Of Feminism” discusses institutions, law, or governance in connection with feminism and gender politics. Even without a dominant policy classification, the article may help researchers identify practical consequences for history, archives, and memory.
Ranked themes and framings
Rank 1 is the dominant inferred theme or framing. Parent labels identify broader theme families; the relationship diagram distinguishes sub-themes, siblings, overlap, and separate-but-related themes.
Themes
- 1Feminism and gender politicsTheme family: Power, ideology, and social conflict100%
- 2History, archives, and memoryTheme family: Knowledge, history, and communication100%
- 3Technology, data, and platformsTheme family: Knowledge, history, and communication33%
- 4Community and organizingTheme family: Identity, culture, and community27%
Academic framing
- 1100%
- 225%
Editorial function
Source topics
These classifications are inferred from article text and source metadata and remain directly editable. Relationship labels express corpus-analysis judgments, not immutable facts.
How “Feminism and gender politics” appears across the Collective corpus
This article was published during the theme’s highest-presence year in the registered corpus (2013).
Relative presence by year
Peak year indexed to 100Presence by member publication
Frequently co-occurring concepts
- Transgender identity and history186
- Community and organizing161
- Violence, safety, and dehumanization112
- Media, rhetoric, and discourse76
- Law and civil rights69
- Culture, identity, and representation68
- Education and youth52
- Healthcare and medicine48
- History, archives, and memory42
- Science, evidence, and expertise33
Academic framings in this topic
Values measure relative presence in the registered Collective corpus, not public search interest or public opinion.
Sources that reference this article
No individual inbound sources have been stored yet. Counts can still appear when a scholarly index supplies aggregate citation metadata.
Coverage combines internal Collective links, verified Webmentions, curated evidence, supported scholarly indexes, and optional public-web discovery. Search-result candidates remain visibly distinct from directly verified links and provider-confirmed citations. This is not an exhaustive index of the public web or of Google Scholar.
Author profiles and related researchers
Related authors in the Collective corpus
Related authors are calculated from co-authorship, shared themes and framings, and citation relationships in the registered corpus. This does not imply a personal or institutional association.
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