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Record W7164152376 · doi:10.5281/zenodo.20632159

Counselling Psychology: The Role Recognition In India

2022· article· en· W7164152376 on OpenAlexaboutno aff
Sargun Bedi, Ravneet Kaur

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typearticle
Languageen
FieldPsychology
TopicCounseling Practices and Supervision
Canadian institutionsnot available
Fundersnot available
KeywordsAccreditationMental healthLicensureProfessional psychologyGovernment (linguistics)Dominance (genetics)Public policy

Abstract

fetched live from OpenAlex

This paper presents a literature review examining the professional status and role recognition of counselling psychology in India. It explores the distinction between counselling psychology and clinical psychology, highlighting how the former remains overshadowed by the latter in the Indian mental health landscape. The study discusses key challenges faced by counselling psychologists in India, including the absence of a governing body, lack of licensure and accreditation frameworks, dominance of western counselling models, and limited public awareness. It further reviews how counselling psychology is positioned in other countries — including the UK, USA, Canada, Greece, Kenya, and Afghanistan — to draw comparative insights for the Indian context. The paper also examines relevant Indian government policy initiatives such as the National Education Policy 2020 and Lok Sabha Bill 301 of 2016, assessing their implications for the recognition of counselling as an independent profession. The authors conclude that counselling psychology in India requires stronger institutional support, independent regulatory bodies, and culturally adapted training frameworks to establish its rightful place in the mental health domain.

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)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.027
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0020.005
Scholarly communication0.0080.003
Open science0.0010.003
Research integrity0.0010.003
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 head0.310
Teacher spread0.254 · 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
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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Same venueZenodo (CERN European Organization for Nuclear Research)Same topicCounseling Practices and SupervisionFrench-language works237,207