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Record W2174600938

Using the self as resource in media production research

2015· article· en· W2174600938 on OpenAlexaboutno aff
Michael Munnik

Bibliographic record

VenueORCA Online Research @Cardiff (Cardiff University) · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsnot available
Fundersnot available
KeywordsReflexivityTransparency (behavior)SociologyPublic relationsMedia studiesHackerEthnographyNegotiationSocial mediaFilter (signal processing)Public spherePhonePolitical scienceSocial scienceLawComputer sciencePolitics
DOInot available

Abstract

fetched live from OpenAlex

This chapter proposes methods for conducting production enquiry at a strained time in the UK media sphere. Whilst scholars mused about whether the Leveson Report and the phone-hacking crimes that preceded it might encourage greater transparency among private news organizations, I argue from experience that public institutions – heretofore perceived as being slightly more open to social research – became reticent in the wake of contemporary problems, not least of which was the scandal concerning former presenter Jimmy Savile. After briefly narrating the challenges I encountered during qualitative fieldwork in Glasgow, I describe the strategies I employed to surmount the challenges and complete the research. The strategy I focus on in this chapter is the inclusion of the ethnographic self as resource. I ground this methodological approach in recent anthropological writings from Collins and Gallinat (2010), who consider it imperative for their discipline. More than reflexivity but less than autobiography, this approach invites researchers to consider themselves among their informants, negotiating access and building rapport but also contributing data and providing a filter through which data are analyzed. I consider the approach with critical reference to examples from literature on media production. I then integrate my prior professional experience as a broadcast journalist in Canada with my research on relationships between journalists and Muslim sources in Scotland. This becomes a template for media researchers with valuable professional experience to make the most of that asset, being bold enough to include it and cautious enough to account for it in a rigorous manner. In this way, anthropological theory continues to advance the ethnographic study of media production.

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.

How this classification was reachedexpand

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)0.016
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0020.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.427
GPT teacher head0.473
Teacher spread0.046 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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