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Record W2547208154 · doi:10.12927/hcq.2016.24793

Canadian Cancer Programs Are Struggling to Invest in Development of Future Leaders: Results of a Pan-Canadian Survey

2016· article· en· W2547208154 on OpenAlexaffabout
Nadir Khan, Lena Ghatage, Peter Craighead

Bibliographic record

VenueHealthcare Quarterly · 2016
Typearticle
Languageen
FieldMedicine
TopicAdvances in Oncology and Radiotherapy
Canadian institutionsBaker Hughes (Canada)Foothills Medical CentreOccupational Cancer Research Centre
Fundersnot available
KeywordsLeadership developmentBest practicePublic relationsPolitical scienceMedical educationMedicine

Abstract

fetched live from OpenAlex

Cancer agencies within Canada operate with a variety of leadership models, assuming that future leaders are identified, developed and supported by institutions other than their own. A literature review, comprehensive survey and structured interviews were conducted to illuminate the perceptions of leadership in Canadian cancer centres. The major finding from the study is the significant gap between the competencies that leaders acknowledge as being important and the lack of development programs for future and current leaders. The study also showed there is agreement on preferred leadership models and the personal traits that identify future leaders worthy of development. Given the current struggles of leadership, the authors suggest that cancer agencies need to strategize how to advance succession planning and leadership development frameworks.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.997
Threshold uncertainty score0.224

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0050.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.056
GPT teacher head0.385
Teacher spread0.329 · 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.

Study designObservational
DomainIncentives
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

Citations5
Published2016
Admission routes2
Has abstractyes

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