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Record W4221045005 · doi:10.21125/inted.2022.1662

VOLUNTEERING AS A TOOL OF SOCIAL INCLUSION AND EDUCATION – CANADA AND SLOVAKIA CASE

2022· article· en· W4221045005 on OpenAlexaboutno aff
Marica Mazurek

Bibliographic record

VenueINTED proceedings · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Behavioral Studies
Canadian institutionsnot available
Fundersnot available
KeywordsInclusion (mineral)Computer scienceSociologySocial science

Abstract

fetched live from OpenAlex

Volunteering in Canada is governed by the legislation – the Code in Partnership with the Canadian Administration of Volunteer Resources (CAVR). Canadian traditions and experience with governing and providing of volunteer activities as well as the perception and importance of volunteering could be beneficial for Europe and Slovakia. Volunteering could become a tool of a stronger participation of seniors at the community activities and life together with the younger generation. It is important for the mutual education and the improvement of life of both generations. The result of co-operation of younger and older people in volunteer activities could lead to the stronger social capital in a community, improvement of quality of life of seniors and the implementation of precious skills and knowledge of seniors for the community development. Volunteering is based on social participation and co-operation of the society motivated by altruistic behavior. Individuals seek to fulfill such goals as to be fully satisfied, recognized, involved in the supportive and helpful activities for the other individuals in need, for community, involved in the creation of social networks and contacts. The contribution’s goal is to explain and analyze the differences of approaches to the motivation of seniors willing to participate at volunteer activities between two continents and two countries of those continents, North America (Canada) and Europe (Slovakia). Seniors are important source of wisdom and experience in the volunteer activities; however there exist obstacles which might hinder the participation of seniors at volunteer activities. Seniors could be on both sides of the supply-demand structure of volunteer activities, which means they could be providers of volunteer activities as well as customers of volunteering. Volunteering is a source of social capital and community development. Canada belongs to one of the most experienced countries in volunteer activities, which are governed by the legislation CAVR (Code in partnership with the Canadian Administrators of Volunteer Resources (CAVR) enabling the volunteer organizations and NGOs to become legally protected and governed. The aim of the study is to discuss the importance of volunteering for the society and define main principles, which have been implemented in the European Union and compare them to those in North America, especially in Canada with the focus at the volunteer activities and their perception among different social groups of volunteers and predominately shedding light at the specific age group – seniors. In order to demonstrate and express the results of the participation of seniors of Canada and Slovakia, secondary research methods have been implemented in the research, especially a thorough content analysis of existing legislation dealing with volunteering activities in Canada and the European Union, academic literature sources and websites dealing with the volunteering content and existing research of motivation online. There have been also used materials collected from the former research publication activities of the author. Due to the fact that the existing statistical data have been collected from the secondary sources existing online (Stat Canada), there is not created full picture on the state of volunteering in Canada, but it gives information only on specific factors in volunteer activities.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.328

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0280.008
Scholarly communication0.0080.002
Open science0.0010.008
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.014
GPT teacher head0.297
Teacher spread0.283 · 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
Published2022
Admission routes1
Has abstractyes

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