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Record W2257945747 · doi:10.14288/1.0055807

School board-public conflict in British Columbia

2010· article· en· W2257945747 on OpenAlexaboutno aff
Ian Julian Cameron

Bibliographic record

VenuecIRcle (University of British Columbia) · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Issues in Education
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical sciencePublic administration

Abstract

fetched live from OpenAlex

The study examined various aspects of school board-public conflict in British Columbia, including the relationships among board operating procedures, the demographic nature of communities, and conflict; issues that lead to conflict; and the intensity of conflict. The study also examined the relationships between community demography and board operating procedures. Board operating procedures were determined by examining the public minutes of all British Columbia school board meetings held during a one year period. Twenty-seven boards, representing a range of procedures, were selected as a sample. Community demographic characteristics were described in terms of heterogeneity, property assessments, and district size. Conflict was measured by means of a questionnaire to board members and district officials. It was found that British Columbia school boards exhibit a wide range of operating procedures, with boards in large districts tending to have less formal contact with the public during board meetings than do boards in smaller districts. The amount of board-public conflict increases as district size increases and is greater in more heterogeneous districts. Conflicts concerning pupil welfare are apt to be intense. Large urban districts experience greater conflict over matters concerning physical plant and instruction than do smaller rural districts. Boards in heterogeneous communities tend to have less conflict with the public if they increase direct contact with the public through public board meetings. Heterogeneity is more closely related to conflict than is district size.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.292
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.012
GPT teacher head0.231
Teacher spread0.218 · 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 designObservational
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
Published2010
Admission routes1
Has abstractyes

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