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Podcast Studies

2022· reference-entry· en· W4283031568 on OpenAlex
Hannah McGregor

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOxford Research Encyclopedia of Literature · 2022
Typereference-entry
Languageen
FieldSocial Sciences
TopicRadio, Podcasts, and Digital Media
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsAmateurMusic industryAffordanceUploadAdvertisingSet (abstract data type)Media studiesSociologyComputer sciencePolitical scienceBusinessWorld Wide WebArtVisual artsLaw

Abstract

fetched live from OpenAlex

Abstract Podcasts are a new kind of digital text that demands new analytical approaches rooted in an understanding of the medium’s history, affordances, and politics. Emerging at the intersection of RSS (Really Simple Syndication) and digital audio technology, podcasts were originally framed as an accessible medium for amateur creators, an audio version of the blog. Although the early technological challenges of both making and downloading podcasts biased the medium toward the same demographic as tech culture (white men), the constant expansion of affordable recording technology and the lack of industry restrictions have led to podcasting’s rapid growth, with Apple announcing that it had reached 2 million podcasts in 2021. While only a small percentage of those podcasts are capable of drawing large-scale audiences, producers have found success catering to microcommunities through highly niche content. The ability to engage communities is enhanced by some of the defining characteristics of podcast aesthetics, namely their parasocial intimacy—that is, the tendency for listeners to think of their favorite podcast hosts as “friends in their ears.” Compared with radio, podcasts are less likely to adhere to professional production standards, and podcasters tend to be less formal and more “chatty” than radio hosts are. While podcasting has amateur and DIY roots, however, the success of true crime podcast Serial has contributed to the formalization of the industry around podcasting networks and a shared set of entrepreneurial practices, largely focused on attracting advertisers or otherwise monetizing shows. Although the most financially successful shows are still disproportionately produced in the United States and hosted by white men, the medium has also continued to diversify. The creation of podcasts that speak directly with and from the perspective of communities drives listenership within those communities, which in turn drives further podcast creation; this pattern can be observed in the expansion of African American podcast production between 2010 and 2020, and similar patterns are evident in Indigenous podcasting, queer and trans podcasting, and both international and non-English-language podcasting. The tendency for podcast listeners to become podcast producers can also be seen in the emergence of new podcasting genres. Serial, for example, has inspired a new genre of audio crime fiction, while WTF with Marc Maron has led to a slew of comedian-hosted interview podcasts characterized by an intimate, confessional tone. The huge range of podcast genres, alongside the broad spectrum of production quality, means that podcasts remain a multifaceted medium—and the scholarship about them is similarly multifaceted. Media studies scholars are interested in questions of what defines podcasting and whether a move away from RSS technology to platform-exclusive shows is signaling the end of the medium’s golden age, whereas those looking at podcast genres are more interested in exploring how podcasting has generated a space for new forms of sound-based storytelling. While the most robust field of podcast scholarship focuses on the use of podcasts for pedagogy, scholars have also begun to theorize podcasting through the act of producing podcasts themselves. The incorporation of podcasting into the landscape of scholarly communication points to how the study of podcasting has the potential to transform not just what scholars study but also how scholars do their work.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.420
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.110
GPT teacher head0.428
Teacher spread0.317 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it