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Record W3084409675 · doi:10.22230/ijepl.2020v16n13a923

Podcasting as a Dissemination Method for a Researcher-Practitioner Partnership

2020· article· en· W3084409675 on OpenAlex

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Education Policy and Leadership · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsnot available
Fundersnot available
KeywordsDisseminationGeneral partnershipInformation DisseminationPublic relationsMetropolitan areaWork (physics)Information sharingSociologyPolitical scienceKnowledge managementComputer scienceMedicineWorld Wide WebEngineering

Abstract

fetched live from OpenAlex

Researcher-practitioner partnerships (RPPs) present opportunities to conduct studies that support evidence-based decision-making for participating school divisions (Coburn, Penuel, & Geil, 2013). Doing this work effectively requires ongoing input from key stakeholders, attention to the local impact of the research, and targeted dissemination to audiences who can benefit from the findings (Tseng, 2012). Research dissemination methods typically include written reports, but constantly evolving media platforms show promise for sharing findings in engaging and innovative ways (Voithofer, 2005). This paper discusses the development and apparent impact of a podcast for a metropolitan RPP to disseminate research findings and other information pertinent to the priorities of partnering school divisions, with implications for broader conversations about exploring issues in public, PK-12 education.

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)0.002
metaresearch head score (Gemma)0.039
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.949
Threshold uncertainty score0.969

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.039
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.369
GPT teacher head0.585
Teacher spread0.216 · 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