Finding the SP of nature in the Qur’an 148

In keeping with the theoretical framework built for this research, it is of importance to give a clear picture of how the present study was conducted according to this methodology to develop a systematic way of finding the SP of natural phenomena in the Qur’an. This system was followed to find SP of nature in the Arabic Qur’an in this research and later used to compare the Arabic Qur’an to its translations. To elaborate, as previously mentioned, the resulting 30 most frequent natural phenomena were examined for their collocations by computing their bigrams via LLR. The bigrams for each term were the ones to consider in this research for two main purposes. The first purpose of finding the bigrams of nature is to extract the lexico-grammatical patterns of nature in the Qur’an, which are the founding blocks of unveiling the subliminal meanings connected with the theme of nature in the Qur’an. The second purpose of employing bigrams of nature in this research was to annotate the evaluative prosodies (EPs) and discourse prosodies (DPs) of natural phenomena in the Qur’an. The percentage of the highest EPs and PDs for each of the nature terms was assigned as its EP and DP. Hence, the exploration of SP was premised on the analysis of both the evaluative and discourse forms of SP via discovering patterns of usage and meanings (as in Sinclair, 2004a and Stubbs, 2007, p.155).

To obtain these meanings after processing the text,218 _{Sinclair's (2003, xvi-xvii) seven-step}

procedure of reading concordances was followed. The steps are as follows:

1- Initiate. This involves examining the lexico-grammatical patterns for each node after collocation extraction in the previous section by looking at the words that occur immediately to the right and left of the node and identifying the highest ranking pattern. Table 21 shows the categorisation of the collocates of nature terms into syntactic sets.

Table 21: A sample of the syntactic categorisation of collocates of natural phenomena

Nouns (n.) Verbs (v.) Adjectives (adj.) Adverbs (adv.)

sign said many indeed

signs sent grateful verily

truth made subservient certainly

dominion praise six

Qur’an say merciful

[Prophet] Lut disbelieve lost

Noah establish spacious

Thamud know evil

Moses judge good

woe created righteous

bounty merge sealed

Pharaoh belong right

throne emerge black

thing assemble white

mischief earth

swallow the warned

sustenance appointed alike

creation send All-Mighty descend All-Wise wronged effort earned prophet paid injustices burden warning witness brother punished worshiper doeth triumph guide ignorance worship promise waste disbelief abode doom pray punishment taste glitter invite glory enter reward reject Eden glorify righteousness give works gave believe remind bliss flow disease understand book spread Adam bow enemy said fire follow creator subjected

Nouns (n.) Verbs (v.) Adjectives (adj.) Adverbs (adv.) blessings come darkness submit light raise bounties warn blast conceal flood drink grapevines drown light split _remember cause

Interpret. After finding the lexico-grammatical (LG) patterns and syntactically categorising

collocates surrounding the nodes, these LG patterns were used to navigate concordance lines and to interpret their meanings when aligned with their verses. For example, it was useful to use concordances via Sketch Engine to navigate the context of the collocation (e.g., bigram) found in the textual analysis of the collocation extractions. An example of the use of copied concordances is shown below in the figure of the Excel sheet, where the word 3رون nwr ‘light’219 _{is analysed. This nature phenomenon Arabic root includes both the}

literal meanings of ‘light’, for example, in words such as ءايض‘translated as light of the sun’ and حيباصم‘translated as lanterns when describing the light of the stars in the sky’ as well

as an attribute of God.220 _{In addition, verified collocates of this root as a token from the}

previous subsection were marked in red in the concordance lines, and the corresponding verses are aligned to the right. With the microanalysis of the word via consultation of the Tafsīr and Asbab Al-Nuzul (e.g., the contexts and occasions of the Revelation of the Qur’an), the SP of natural phenomena in the Qur’an was explored.

Figure 30: A concordance of the nature term light in the Qur’an

219The number ‘3’ next to the Arabic word in the figurerepresents the root-disambiguation of the word (See also Section 4.1.2). 220See also the Quranic Arabic Corpus, Available from : http://corpus.quran.com/search.jsp?q=light

However, since many concordance searches of nature terms in this research can produce hundreds of lines in the Qur’an datasets (source text and target texts), this zresearch follows Sinclair (1999) in selecting 30 random lines in which the statistically significant bigrams appear and noting patterns in them, then selecting a different 30, noting the new patterns, and so on until a further selection of 30 lines reveals nothing new (Baker et al., 2006, p.44). This is done to perform a content analysis to interpret the meanings of the co-occurrences of nature in the Qur’an. Thus, the analysis of the first 30 concordance lines for the nature terms helps in forming a hypothesis that may link repeated words (e.g., they are from the same word class or have similar meanings). Their link was generally established by categorising the meanings into categories.

2- Consolidate. This means looking for other evidence (other collocations) to support the hypothesis formed from the first 30 lines of the concordance in Step 2, extending beyond the word positions first studied and revising the hypothesis by looking at the next 30 concordance lines of patterns of natural phenomena. This was done by conducting a form of content analysis of nature in the Qur’an to elicit the pragmatic functions221 _{of the lexico-grammatical patterns of natural phenomena (See figure}

below and for details and examples see qualitative analysis in sub-section 4.1.5).

Figure 31: The discourse prosodies of the word light

3- Report. It means the labelling of the evaluative prosodies for each of the patterns of natural phenomenon as being positive, negative, or neutral based on the acquired connotative meanings from the co-text222 _{in each of the co-occurrences. Figure 32}

221 Pragmatic functions are also referred to as discourse prosodies in this thesis.

shows three different SP meanings of the word water.223 _{It can have positive and}

negative EPs when its neighbouring collocates, such as ‘tidings’, ‘send’, and ‘scalding’ respectively refer to the emphasis on the message of the Qur’an, glorifying God and his creation, and punishment in the afterlife.224

Figure 32: The discourse prosodies of the word water

The following step was to manually annotate the verses in which these patterns occur with the appropriate evaluative and discourse prosodies for each of the nature terms in the Qur’an. It should be noted that when calculating the evaluative and discourse prosodies of nature terms, it was necessary to go back to the contextual meanings of the terms and consult the Tafsīr of the verses for the further assertion of the meanings and to avoid subjectivity.

4- Recycle. This step means starting with the next most important pattern nearest to the node and looking for anything unusual in any remaining data.

5- Results. The manually calculated SP of nature in the Qur’an (the percentage of the evaluative and discourse prosodies for each of the natural phenomena) was reported (See also quantitative analysis in section 4.1.5). The highest percentage of EPs and DPs for each natural phenomenon word is said to be its evaluative prosody and discourse prosody. For example, Figure 33 illustrates the different pragmatic functions of the words people, day, sky/heavens, earth, and water in the Arabic dataset. Their discourse prosodies meanings or pragmatic functions were found by

223 Translation of 1997. Ṣaḥīḥ International The Qur'an: Arabic Text with Corresponding English Meanings. Riyadh: Abul-Qasim PublishingHouse.

calculating the percentage of the DPs over the total frequencies of each of the words in the text.

Figure 33: A dataset of the pragmatic functions to find discourse SP in the Arabic text

6- Repeat. In this step, a new selection of data (30 concordance lines of another natural phenomenon term) from the corpus is taken, and the same steps of reporting the analysis are followed.

The following section will discuss the types of analyses employed to explore the SP of nature as a theme in the Qur’an with examples.