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Record W6912976715 · doi:10.5518/1588

PSM-AP Comparative document analysis data: Priorities and challenges in the policy and digital strategies of ten PSM

2024· dataset· en· W6912976715 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Leeds · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
FundersHORIZON EUROPE Research Infrastructures
KeywordsKey (lock)PersonalizationWork (physics)Digital mediaPublic policyService (business)

Abstract

fetched live from OpenAlex

The document consists of a list of 61 key policy and strategy documents analysed as part of the comparative work conducted in WP1 of the project Public Service Media in the Age of Platforms (PSM-AP). It also contains a series of selected quotes supporting the three key areas prioritised by the policies and PSM digital strategies: People (reaching audiences), Personalisation (developing the video-on-demand portal), and Prominence (of PSM services and content). The data was collected and analysed in 2023, from documents concerning 10 PSM organisations in seven media markets: Belgium-Flanders (VRT), Belgium-Wallonia Brussels (RTBF), Canada (CBC/Radio-Canada), Denmark (DR, TV 2) Italy (RAI), Poland (TVP), and the UK (BBC, Channel 4, ITV). All quotes were translated to English by the authors.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.249
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.090
GPT teacher head0.312
Teacher spread0.222 · 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
GenreDataset

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
Published2024
Admission routes1
Has abstractyes

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