MétaCan
Menu
Back to cohort
Record W7132999769

The Fourth Estate in the Sixth Grade: Exploring "News" in the Lives of Canadian Pre-teens Through Creative Media Inquiry

2014· dissertation· W7132999769 on OpenAlexaboutno aff
Ruth Averie Macdonald

Bibliographic record

VenueTSpace · 2014
Typedissertation
Language
FieldArts and Humanities
TopicLiteracy, Media, and Education
Canadian institutionsnot available
Fundersnot available
KeywordsFourth EstateNews mediaRelation (database)Face (sociological concept)Class (philosophy)
DOInot available

Abstract

fetched live from OpenAlex

This thesis explores how young people conceive of and engage with news in the current Canadian context. It suggests the need to transcend notions of youth as either "disengaged" or "disenfranchised" in relation to news by exploring questions such as "what counts as 'news'?" and "what does news engagement look like?" The study involved one class of Grade Six students (n=26) in the Greater Toronto Area in a mix of participatory, creative activities and interviews. The results illustrated participants' diverse ways of defining news or "news vocabularies" and the importance of friends and family members to the "news ecologies" they live in and interact with. Results also demonstrated the unique complexities pre-teens face in their relationships with news. Overall, this thesis calls for further critical thinking around how Canadian society understands young people as news users, and how young people utilize news to reproduce and transform the cultures they inhabit.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.383

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0290.014
Scholarly communication0.0130.004
Open science0.0020.005
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.126
GPT teacher head0.341
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueTSpaceSame topicLiteracy, Media, and EducationFrench-language works237,207