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Record W7052874357

Socialt arbete bedrivet av ideella organisationer i Kanada- och deras sätt för att uppfylla sina uppdrag

2009· other· en· W7052874357 on OpenAlexaboutno aff

Bibliographic record

VenueLund University Publications Student Papers (Lund University) · 2009
Typeother
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)Knowledge sharingDependency (UML)Qualitative researchPublic sectorCore (optical fiber)Field (mathematics)Social responsibility
DOInot available

Abstract

fetched live from OpenAlex

This study aims to highlight conditions for some selected non-profit organizations providing social services in Toronto, Canada. The essay is a case study which includes literature studies, field observations and interviews with respondents working in the non-profit sector. The analyses are mainly based on qualitative semi structured interviews with respondents working in non-profit organizations sharing their knowledge about their organization. The selected organizations share a responsibility with the public sector in providing social services and this study try to problemtize this. Some findings this study accompanied to show was that one challenge for the non-profit organizations was to get enough financial resources for the work they aim to do. Financing and to get resources for the organizations core expenses was especially something the organizations struggles with. The organizations also lend on their dependency for voluntary engagement. Distinct for a non-profit organization is that they often have a specific purpose or mission with their organization, even though the mission can be a vague.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.230
Threshold uncertainty score0.462

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0230.010
Scholarly communication0.0090.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.001

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 head0.008
GPT teacher head0.223
Teacher spread0.215 · 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 designQualitative
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
Published2009
Admission routes1
Has abstractyes

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