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Record W2792907750 · doi:10.24124/2010/bpgub1447

UNBC English language studies: strategic management plan for sustainable growth

2010· dissertation· en· W2792907750 on OpenAlexafffund
Paul Duh Huei Pan

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicStrategic Planning and Analysis
Canadian institutionsUniversity of Northern British Columbia
FundersUniversity of Northern British Columbia
KeywordsSWOT analysisStrategic planningSustainabilityPlan (archaeology)Order (exchange)Process managementBusinessTerm (time)Strategic managementSmart growthEngineeringEngineering managementEnvironmental planningOperations managementEnvironmental resource managementGeographyLand useMarketingEconomicsFinanceEcologyCivil engineering

Abstract

fetched live from OpenAlex

The University of Northern British Columbia's English Language Studies program has experienced rapid growth over the past year. If this trend continues, the program will become unsustainable. In order for the program to sustain growth into the future, a strategic plan needs to be developed. This project conducts an environmental scan of the ELS program utilizing Porter's Five Forces, PEST, and SWOT analysis and a comparative analysis of other post-secondary ESL programs to identify key strategies and major challenges facing the ELS program today. Recommendations are made for the strategic development and formulation of the program. Short-and long-term strategies are derived from the recommendations. In order for the ELS program to grow sustainably, management should immediately implement a short-term strategic plan and examine long-term differentiations strategy for future growth. --P. ii.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: Other · Consensus signal: Other
Teacher disagreement score0.979
Threshold uncertainty score0.539

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.001
Scholarly communication0.0060.001
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0250.005

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 head0.023
GPT teacher head0.273
Teacher spread0.250 · 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 designNot applicable
Domainnot available
GenreOther

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 routes2
Has abstractyes

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