Filmmaker Kevin Smith Loves Brazilian Transsexuals!
At least that’s the comment he made on Twitter: Are you Brazillian (sp)? I’m only into Brazillian (sp) Trannies. Pre-op. As I’ve stated before, I think celebrities that make these kind of jokes will reap what they sow in comments around the internet. Celebrity sites will report what the star joked about in jest as a fact, not as humor. Lady Gaga is the perfect example of this (from The Sun): “She also said in a recent web blog: ‘I have both male and female genitalia, but I consider myself a female.’ But GaGa, 23, told Oz’s Matt and Jo show: ‘I’ve made fun of it before but to talk about it is ridiculous.’ Hopefully she’ll learn that making fun of people who already battle ugly stereotypes isn’t nice, isn’t good business, and isn’t funny. I’m a fan of Smith’s movies, so I know there’s not a lot of hope
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
“Filmmaker Kevin Smith Loves Brazilian Transsexuals!” may matter to community readers because it preserves a first-person or testimonial account connected to technology, data, and platforms, while also engaging sex and gender classification. Such accounts can document how an issue was understood and experienced from within the period or community being discussed.
Historical significance
As a publication record from 2009 at Transadvocate.com, “Filmmaker Kevin Smith Loves Brazilian Transsexuals!” provides dated evidence of how technology, data, and platforms was being argued in relation to sex and gender classification. Comparing it with earlier and later records can reveal changes in vocabulary, evidence, and emphasis.
Policy significance
No dominant policy frame was detected in “Filmmaker Kevin Smith Loves Brazilian Transsexuals!.” Its policy relevance, when present, is therefore likely indirect: the article’s treatment of technology, data, and platforms may shape later arguments about institutions or public practice rather than proposing a specific rule.
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
- 1Technology, data, and platformsTheme family: Knowledge, history, and communication100%
- 2Sex and gender classificationTheme family: Power, ideology, and social conflict50%
Academic framing
- 1100%
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 “Technology, data, and platforms” appears across the Collective corpus
This article appeared 4 year(s) before the theme reached its highest annual presence in the registered corpus in 2013.
Relative presence by year
Peak year indexed to 100Presence by member publication
Frequently co-occurring concepts
- Transgender identity and history45
- Community and organizing37
- Media, rhetoric, and discourse21
- Law and civil rights20
- Feminism and gender politics15
- Healthcare and medicine15
- Violence, safety, and dehumanization14
- Culture, identity, and representation13
- History, archives, and memory13
- Science, evidence, and expertise11
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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