MétaCan
Menu
Back to cohort

The Framework and Measure of Effective School Visioning Strategy (MCP-FIV)

2003· article· en· W53488582 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

VenueAlberta Journal of Educational Research · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Communication Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMeasure (data warehouse)PsychologyMathematics educationComputer scienceData mining

Abstract

fetched live from OpenAlex

This article describes a pilot study in which a prototype instrument is presented as a first step toward a reliable and valid tool that facilitates both the establishment of a visioning strategy and evaluation of the effectiveness of visioning strategies, existing or new. A brief historical perspective precedes an examination of the actual steps that comprise a visioning strategy. Analysis of research data arising from a pilot study involving the instrument suggests that school leaders are more likely to be involved in visioning strategy than parents or students. All stakeholders generally, and parents, students, and principals specifically, are more likely to be involved in visioning processes in medium-sized schools. School leaders will be challenged to consider whether change in their schools is consistent with vision that has been inclusively and collaboratively established or if such change reflects centralized, mandated, top-down processes that are simply implemented by principals.

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)0.005
metaresearch head score (Gemma)0.063
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.797
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.063
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.109
GPT teacher head0.498
Teacher spread0.389 · 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