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Record W1997648537 · doi:10.1177/0095399707303635

Public Agencies and Collaborative Management Approaches

2007· article· en· W1997648537 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.

Bibliographic record

VenueAdministration & Society · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsResistance (ecology)SocializationPublic relationsCitizen journalismBusinessPerceptionParticipatory managementForest managementKnowledge managementPolitical sciencePsychologySocial psychologyComputer scienceForestryGeographyEcology

Abstract

fetched live from OpenAlex

Resistance among administrative professionals to participatory approaches is analyzed by means of a case study involving the implementation of community-based forest management (CBFM) in India. The model consists of two dimensions of attitudinal resistance to change—disapproval of CBFM regime by forest managers (a) at individual level and (b) at organizational level—and four categories of factors influencing resistance: personality traits, organizational factors, external environmental factors, and socialization factors. The model is empirically tested using the perceptions of forest managers working in state Forest Departments of four states in India. The empirical findings are used to suggest strengthening of organization and public administration theories on four aspects and to suggest some specific measures to deal with the attitudinal inertia of public administrators.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.543
Threshold uncertainty score0.722

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.055
GPT teacher head0.256
Teacher spread0.201 · 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