MétaCan
Menu
Back to cohort
Record W2112793374 · doi:10.26522/tl.v4i1.10

Coffee and Collaboration: A Tean Approach to Talking Learner Challenges

2007· article· en· W2112793374 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueTeaching and Learning · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicCollaborative Teaching and Inclusion
Canadian institutionsUniversity of VictoriaBrock University
Fundersnot available
KeywordsExcellenceContext (archaeology)Christian ministryLiteracyPedagogyPsychologyMathematics educationPublic relationsPolitical scienceGeography

Abstract

fetched live from OpenAlex

The focus of this issue of Teaching and Learning, "Boys and Literacy," is an example of an education concern defined within the context of "authentic inclusive schooling and excellence for all" as defined by the Ontario Ministry of Education. Professionals interested in improving achievement and performance objectives related to student and school based learning and who regularly seek out opportunities to engage in group discussion and collaboration are often able to bring about change within the education environments they are employed. In the instance at hand, boys and literacy it is now more fully understood that beside planning for the host of learner contingencies that contribute to an individual learner profile, gender and socio economic influences and or differences need to be understood within the context of identifying learner challenges and needs. And that they be interpreted and represented in terms of successful classroom practices.

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)0.009
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.632
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.325
Teacher spread0.297 · 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